Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos |
![GitHub](https://camo.githubusercontent.com/e96b21d37d17d6a68d8977a00be2f78edceca5a7f82c2c08e7436ebe7477940b/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f5448552d4c594a2d4c61622f41522d5365673f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/6167d957620ccbfc714cfcbe8d8dcf4fac7e6988436e2be0bf14309d3be73e48/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30373232342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Vision Transformers are Good Mask Auto-Labelers |
![GitHub](https://camo.githubusercontent.com/c7eb4c714502a8b4772cae6a24b741d17a8a5fe4feb96567a35f895594ef8d49/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4e566c6162732f6d61736b2d6175746f2d6c6162656c65723f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/781cb05d371dc9af00e10e5f837e5b0c6114f21041896cf37636cf49c4ac5fb9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330312e30333939322d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Visual Recognition by Request |
![GitHub](https://camo.githubusercontent.com/be5ea53ed598c181db38f53193aa3a893ede7b50ef94186bc156b3544b753d51/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f63687566656e67742f56697375616c2d5265636f676e6974696f6e2d62792d526571756573743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/2af677a4e9c8f0e660bca03e9018cd2ef0e83c102f1de673991a608e0e3b86d1/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323230372e31343232372d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark |
![GitHub](https://camo.githubusercontent.com/42a0540fe3202ef6e58248e34e34640c6cf7942d634e4f5b3ff254158e57940a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6a616e6b7965652f555255523f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/f51f7abef6b262226db6c2ebb33ff49f826f888b9b355320adf49c93ccb15966/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330352e31303839392d6233316231622e737667) |
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AttentionShift: Iteratively Estimated Part-based Attention Map for Pointly Supervised Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/f9c81cbb812304d03aa4eea1068edf8694ebe47cb8d702a29a6b8783c0d802c2/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4d696e675869616e674c2f417474656e74696f6e53686966743f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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MDQE: Mining Discriminative Query Embeddings to Segment Occluded Instances on Challenging Videos |
![GitHub](https://camo.githubusercontent.com/e6f36b5c6b108c3f57c5fcdc7fd87e23357f83639ed1bce25ca399360a009e80/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4d696e6768616e4c692f4d4451455f43565052323032333f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/08846e9b33e4054821a5d9d570feab3fce237bb84713f9f09597d4c61869e1ac/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31343339352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Look Before You Match: Instance Understanding Matters in Video Object Segmentation |
➖ |
![arXiv](https://camo.githubusercontent.com/d12101df56b1710c2f61fcc93b140b6d25d771143b8f4d577dd70ebad4262e61/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e30363832362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
SIM: Semantic-Aware Instance Mask Generation for Box-Supervised Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/e4b146545a84bea60e54f3a5491d1f87a5e51b970b6077f7bb39a0c9b43e2189/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6c736c72682f53494d3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/5fec342b169267b58115ebe6ede7fcf3f34f0d31cb41baba069fe66c40a0d068/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30383537382d6233316231622e737667) |
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EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation without Scene Supervision |
![GitHub](https://camo.githubusercontent.com/1621e04ce7a034095cf16e3ad2a5363938618757fe6506204bf723a90e9fb7f1/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4a69616875694c65692f4546454d3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/7fb3bcbae24ff7183dc8f3556bd9b03206d086b697d26b371775b8bcf7f9bf59/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31353434302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Camouflaged Object Detection with Feature Decomposition and Edge Reconstruction |
![GitHub](https://camo.githubusercontent.com/719a526d4aada88f3a483e9cb3968a7db1c3dcedf06a058b8e5f864d8e42bf82/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4368756e6d696e6748652f46454445523f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding |
![GitHub](https://camo.githubusercontent.com/2da3db11bf8de8a1d466e76463fb2638ba6aafa2ea017c17e54c893e78fb7420/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f52656167616e313331312f4c4f434154453f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/04810e0258950dbee7829cd969237b93b0bca43afefb54dc33a4f087e8550fcb/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30393636352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
OneFormer: One Transformer to Rule Universal Image Segmentation |
![Hugging Face](https://camo.githubusercontent.com/c3465e25cd7820134edd8dad479dfcb20e49c7cb4a8d333b08ed0fdfead962d3/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f2546302539462541342539372d64656d6f2d4646443231462e737667) |
![arXiv](https://camo.githubusercontent.com/69d386eafaa8da9f04df61897b527c708452166e7a8132633e9dea2d370fcf5d/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231312e30363232302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Mask-Free Video Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/0dfc4f76c5476e231b29d4749d7283eebafcfdaddcf4b7fc7c0a2bb02d44235f/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f53797343562f4d61736b467265655649533f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/729e40715d96050b21a6276a3f472c9ffe66ef498647ff31df92f85453e02b86/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31353930342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Less is more: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/e124281902c743edcba343e6ed17c78d2e5b4ba59ce339424f24066a1e414ab6/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6c31393937692f6c696d33643f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/28421b42231df34510064253b6908f8d12f407bab55da2980f385e0e063cc62a/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31313230332d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
InstMove: Instance Motion for Object-Centric Video Segmentation |
![GitHub](https://camo.githubusercontent.com/1b066c82911341701cf41633c09f66bb0108ccae82248c017c83ece00518ef6d/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f776a66353230332f564e6578743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/bf37905ed1cbc4fb58f22678a09747ff446066110dce39e5636089b201887771/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30383133322d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation |
![GitHub](https://camo.githubusercontent.com/c25d9befb7bd02593462821ce8925237289d2a005876877e5f9b8778d9cb038a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f636c6f766161692f506f696e7457535349533f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/34c67fcc22cebebb0fbdc9a3ff78311c9996dec702a946d560cdfa246771eb66/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31353036322d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Edge-Aware Regional Message Passing Controller for Image Forgery Localization |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Interactive Segmentation as Gaussion Process Classification ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/d54ecd41a00c1a504f586edb1f2c75d6de9b451cb89a980e5cfb7f75f94f3ccc/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7a6d68686d7a2f47504349535f43565052323032333f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/a6beb696334a5a02a3acde708d32d79c28d6ff17d285afa705ee0213dbb094bd/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330322e31343537382d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Semantic-Promoted Debiasing and Background Disambiguation for Zero-Shot Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/e8d1a5b3b1c0a6ef74f750e90a82e2f009e069073a35f2597963c11af021519e/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f686573687574696e673535352f44325a65726f3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/14535431b693617afe9392e94114a1bc93ef1233da43a33070a4741bc622d6a4/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330352e31333137332d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Adversarially Masking Synthetic to Mimic Real: Adaptive Noise Injection for Point Cloud Segmentation Adaptation |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Generative Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/f3bc61ea6c7dad0e1b8184a5fb5e266beadcf1c2772627927e7d84f46f39b608/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f667564616e2d7a76672f4753533f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/e2f24003cc2b86aaa3773aab906b6dba31b6f55d1013d6876e095480a2c27f3f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31313331362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Modeling the Distributional Uncertainty for Salient Object Detection Models |
![GitHub](https://camo.githubusercontent.com/db36cc90470e823d1cab8b004e0628d2941e752b2d07fce1c47a828b8885e24f/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7478796e7770752f446973747269627574696f6e616c5f756e6365727461696e74795f534f443f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Simultaneously Short- and Long-Term Temporal Modeling for Semi-Supervised Video Semantic Segmentation |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/0247040af2d1da824c42c159cf8919e306b1f3919ec7e6f2a691c76ed7a608aa/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f73656e6e6e6e6e2f4f75742d6f662d43616e6469646174652d52656374696669636174696f6e3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/30e12d7891bd91df6f90e0f7381b4e0034ffe4d2c1b2574168beff33af75a95a/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231312e31323236382d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
DynaMask: Dynamic Mask Selection for Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/afc2bd2d426342349bea4cd133d5b2d2e90041457f9ab051121b63e38b26688e/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6c736c72682f44796e614d61736b3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/71bd0dabc6028a939640c3623b27a8d8329f9b6733281512c0ad72ee70c3ce15/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30373836382d6233316231622e737667) |
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MSeg3D: Multi-Modal 3D Semantic Segmentation for Autonomous Driving |
![GitHub](https://camo.githubusercontent.com/2b4de277827afba1174edc61c97e284cb51e9d270a3037d488c6a77cdcb345e4/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6a69616c656c69312f6c6964617273656733643f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/65564a73afc4f84d8cc7a0b541eae773485c57ab6fdfb961050b0c915e7cd1a1/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30383630302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Generalizable Local Feature Pre-Training for Deformable Shape Analysis ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/0f91c3b0885d0d28c6d44de6fb437076f9331665c9f1e039b765abfef3a62b97/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f70766e69656f2f76616465723f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/c35c0371e3fda7c667fa996e583e2e0a37f7dd5e02ca51eab71896841ad09dec/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31353130342d6233316231622e737667) |
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Understanding and Improving Features Learned in Deep Functional Maps ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/67026892fde9fe76c06b0a31f262b74e6ff65fee275311eb20f0b92ecfae918a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f70766e69656f2f636c6f7665723f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/215139648957914403f1df06fdb3d07f7cfc599f43cfa8d96140124b2c847145/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31363532372d6233316231622e737667) |
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G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors |
![GitHub](https://camo.githubusercontent.com/d9660a44e59e7ab263b60d10fb53dcfa153d26e00dda796833ea9d7f6f5bcf0a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6d617276696e2d656973656e6265726765722f676d736d2d6d61746368696e673f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/ccf19d210ff78cde9c38a80bbb8fffe26f92987280a84ade4f1b273aae06f565/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e30323931302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Continual Semantic Segmentation with Automatic Memory Sample Selection |
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![arXiv](https://camo.githubusercontent.com/76921604f2525d3ab2d8d98c320954365ade4580c0f34f56bd3d446f94738712/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330342e30353031352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation |
![GitHub](https://camo.githubusercontent.com/a7892998ec6e049c4cdd64a95490a258aee05cb2d44b5a02e55dae6f8169cdcf/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6279746564616e63652f467265655365673f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/56acfc96b45dcfc14938a09d0b1a6977f45ed97a72557b6bac9a3179eeade52a/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31373232352d6233316231622e737667) |
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Object Discovery from Motion-Guided Tokens |
![GitHub](https://camo.githubusercontent.com/2c261eef015066759009fb99fdcccb182e51a08c98c8771c9105ae9d1c7c0c0c/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7a7062616f2f4d6f546f6b3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/138cfb1acce09d8891410d3d9861d2cef125c5c8a6c37fcf9277dd1f43a4d947/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31353535352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Efficient Mask Correction for Click-based Interactive Image Segmentation |
![GitHub](https://camo.githubusercontent.com/26c2eb41d377054f433223b781faa726cd4a26e22695467f365687a2fc3d5313/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f666569617879742f454d432d436c69636b3f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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Balancing Logit Variation for Long-Tailed Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/78816bd416576807a067b87d8c62766c96bba6dbef4afbf0a44f3face8ed707d/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6772616e74776f7264382f424c563f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/e152bfff07af7e6fd7dbe15e6fc08c36fa236dfdb1c5bc3aa61964f629e36199/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330362e30323036312d6233316231622e737667) |
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Fuzzy Positive Learning for Semi-Supervised Semantic Segmentation |
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![arXiv](https://camo.githubusercontent.com/5a8ca1ebe073638ff3c025d3453e15f99a83ee5c125354aba7537648aa26f5f3/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231302e30383531392d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Learning Open-Vocabulary Semantic Segmentation Models from Natural Language Supervision |
![GitHub](https://camo.githubusercontent.com/0bcdf37beef9cd167833b4d563bb7b3b67e1bd6d498dba686073b7c19e9f5b53/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4a617a7a636861726c65732f4f565365676d656e746f723f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/b07728bbf7686e3beb423a512adea27e555bae53417e6e04f575db6ece262293/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330312e30393132312d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Improving Graph Representation for Point Cloud Segmentation via Attentive Filtering |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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BUOL: A Bottom-Up Framework with Occupancy-Aware Lifting for Panoptic 3D Scene Reconstruction from a Single Image |
![GitHub](https://camo.githubusercontent.com/b17a18b252ff9865958299086e13f3aeb72b18cb2a70b141e5d9ce68c540e275/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f63687473792f62756f6c3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/e5c93f5c403456e6a517cc06685a1f3e0c57785892f89b7afa7c1c93be59195b/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330362e30303936352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub Page](https://camo.githubusercontent.com/1d553b1d08bbbe375bd4742184674434cc4f6ca75c8293238dcc7d5b6202674a/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f4769744875622d506167652d3135393935372e737667) |
![arXiv](https://camo.githubusercontent.com/bc4c58fc9e928780bff2c82365b5029f2bf95d950ea876b59c04a2eb95e6f729/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231302e30353934342d6233316231622e737667) |
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CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes |
![GitHub](https://camo.githubusercontent.com/3dac8f0d1f9e81aebde12b3bb71447a2aa81bee0589fe837e670c57d0833ff26/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4861727368696c4268617469612f434375616e74754d4d3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/3620d20f54c6fe861ee31d703eff2dc2f02fa092f6ea6c5d39cf490e964bc437/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31363230322d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Hierarchical Dense Correlation Distillation for Few-Shot Segmentation ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/6883e6d7f9d42632b6617484ca1ad939b78886e6821763a001c994645b3ca48a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f50626968616f2f48444d4e65743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/cd9aea937627353e3b162e8a4113f0ab67b5347d7e6d945698ecd70d279d40ae/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31343635322d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
UniDAformer: Unified Domain Adaptive Panoptic Segmentation Transformer via Hierarchical Mask Calibration |
➖ |
![arXiv](https://camo.githubusercontent.com/03c5715d8437cf669ff813133ee3bde6e7349086cddbffec2e5cb804b7301f9b/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323230362e31353038332d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation |
➖ |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Understanding Imbalanced Semantic Segmentation through Neural Collapse |
![GitHub](https://camo.githubusercontent.com/024d900f87009bd3dc06a0b0326cf1027cf1cffcd60fc8ea9bbdc809ca270bb3/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4e657572616c436f6c6c617073654170706c69636174696f6e732f53656d616e7469632d5365676d656e746174696f6e3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/fa4b4373a4897eb620472dc10fd770e26dd41ba920cff2b7516214a53c491895/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330312e30313130302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/f4baa3ec2434179bfc53fef3928fb466995d143e1221504e79489b1027bdd06d/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4c696865596f756e672f556e694d617463683f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/ca58fbd74b0f9fa7fe979348d21438b6b456cd2440b7f4796dbe89c4dc86e12e/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323230382e30393931302d6233316231622e737667) |
➖ |
PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models |
![Google Drive](https://camo.githubusercontent.com/bad062ec48c13d9f08f41241253940107c6fb33831453ee50f79aad50c17ba9e/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f476f6f676c6525323044726976652d3432383546343f7374796c653d666f722d7468652d6261646765266c6f676f3d676f6f676c656472697665266c6f676f436f6c6f723d7768697465) |
![arXiv](https://camo.githubusercontent.com/837a2f3d69f63e743e249dc37d82f34ba33da5620ff5657412b082395e8980ba/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e30313535382d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
PartDistillation: Learning Parts from Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/56ea8baf763236c7f7094ef84589357b912019c13527298b9403b06f49138be4/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f66616365626f6f6b72657365617263682f5061727444697374696c6c6174696f6e3f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Sketch2Saliency: Learning to Detect Salient Objects from Human Drawings |
![GitHub](https://camo.githubusercontent.com/be28f5450bf1e109e79ef447880995829a20f1d9a88732169aaa7b25d1b294ce/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4179616e4b756d61724268756e69612f536b657463683253616c69656e63793f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/29486152c1e3e4496f0ab3d1e1e3b1e48b9e86ffda096f4f27f3c5eae1d70e1f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31313530322d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
FastInst: A Simple Query-based Model for Real-Time Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/114e797b1b931b60462b8bb811f8c4dbebedc2e211398277b51bad0a7cf454f4/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6a756e6a6965686539362f46617374496e73743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/63cec9299a23e39278fd6292b100284aae165179962764d30c7a46dc95d68a8f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30383539342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
SemiCVT: Semi-Supervised Convolutional Vision Transformer for Semantic Segmentation |
➖ |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
➖ |
Semantic Human Parsing via Scalable Semantic Transfer Over Multiple Label Domains |
![GitHub](https://camo.githubusercontent.com/56cf56ff51ec5f4c6fe7853211c6d51dfd1ed233a1b86d3dc12c8e0d3c4dff51/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f79616e676a69652d63762f5353543f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/4f1db9b8c5b821ca7bd10eb9066893a6031f730a23661d45eb9bb1945815e8a3/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330342e30343134302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Open-Set Semantic Segmentation for Point Clouds via Adversarial Prototype Framework |
➖ |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Hunting Sparsity: Density-Guided Contrastive Learning for Semi-Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/56be3bd352ceb31de7df181b618f686c81c7cd1f4a27c3736d86a4604498b184/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f476176696e7778792f4447434c3f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
➖ |
A Generalized Framework for Video Instance Segmentation |
![GitHub](https://camo.githubusercontent.com/1f545773166031de806de6c2b95721979ee1a7bb491c6b20b224fc789fde11ee/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6d6972616e68656f2f47656e5649533f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/7276731472ace48233f592ac7e53aba022a643c9a6132a5fd992b51d734a4801/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231312e30383833342d6233316231622e737667) |
➖ |
SimpSON: Simplifying Photo Cleanup with Single-Click Distracting Object Segmentation Network |
![GitHub](https://camo.githubusercontent.com/87b39fcfe8ab7a5be11567e381bd805acec4219dffca3d91fa4ce245f1248a36/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f686d6368756f6e672f53696d70534f4e3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/f36b48feb22dabdbc50c824f6deb88ee86d8b5573e9f0780399403f0e55f1fb1/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330352e31373632342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Complete-to-Partial 4D Distillation for Self-Supervised Point Cloud Sequence Representation Learning |
![GitHub](https://camo.githubusercontent.com/7d6efefd977ee3f21b8a9488f01339d014593dfd2de94a63a62ed6d43bf3d569/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f646f6e67796832302f4332503f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/fa332f0b8e5ed690a1865a4e8c7b13b3d3a871d89a5dee73e365e77a630437ec/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e30353333302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Self-Supervised Learning for Multimodal Non-Rigid 3D Shape Matching ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/cda292c07d65245744b44c25163c33331cf51df064be16ddca2bc8729fa506c9/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f646f6e676c69616e6763616f2f53656c662d537570657276697365642d4d756c74696d6f64616c2d53686170652d4d61746368696e673f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/91dd466ec4435b9129e429c8067a8ed8d41ba45fac2f14b29e60a2786896c2f5/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31303937312d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Ultrahigh Resolution Image/Video Matting with Spatio-Temporal Sparsity |
![GitHub](https://camo.githubusercontent.com/0bd697a00b731126fc2b53d3a22780c9feee1ed447bf29f670a553480ac53ef2/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6e6f7773796e2f7370617273656d61743f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
➖ |
Style Projected Clustering for Domain Generalized Semantic Segmentation |
![Gitee](https://camo.githubusercontent.com/e217c61a81c270cf4b129f2838032144103426162e0d8fc17197c3074dcb63cb/68747470733a2f2f67697465652e636f6d2f6d696e6473706f72652f6d6f64656c732f62616467652f737461722e7376673f7468656d653d6461726b) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds |
![GitHub](https://camo.githubusercontent.com/0a52c61749d05794e9da3d287c00384bf8daefe98d79281a7ab6a9a0f37ff697/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f43564d492d4c61622f4d61725333443f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/c1753b91890428b7df81316b4a9801f1cb742fcd4125b2f36621500dc176dc89/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330372e30393331362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Compositor: Bottom-Up Clustering and Compositing for Robust Part and Object Segmentation |
![GitHub](https://camo.githubusercontent.com/eedaf52a235cba15123762384454e6ca0f75b4165178f4f8716f512d68c38d0f/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f5441434a752f436f6d706f7369746f723f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/9f848194cf1fb321aba7d984d7b6d4b5605a0c017631c2cd70195c278e1e0845/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330362e30373430342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Dynamic Focus-Aware Positional Queries for Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/18946e93bf6605e648fcb91287dc709cc98569877ce3fdc52fe9e8628727d6a6/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7a69706c61622f46415365673f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/6de4bf71a254b4bf6e11e8f5c3d66d97fdd23fe310285e151029fbc01f90f7ad/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323230342e30313234342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/5862592cd15c0c1500a5f9eb837b66aa2ac2d242dfeb929b8e1ab17941b89ece/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f64696e676a69616e73773130312f4847466f726d65723f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/720cf70aba4b1d7069e4979dd58e3ba8d3fdde4be201771388bf6b4ecc6f7f49/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330352e31333033312d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Marching-Primitives: Shape Abstraction from Signed Distance Function ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/1a7651a6de439d041b68fe66dd69884d46bf5c1dce3c70c10a16cfbb1801c61c/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f43686972696b6a69616e4c61622f4d61726368696e672d5072696d6974697665733f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/75f71f3356bd3755a6c76600a4043915dce25a4c5672979835af52b4d7fff662/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31333139302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Multimodal Industrial Anomaly Detection via Hybrid Fusion |
![GitHub](https://camo.githubusercontent.com/6158e18321b57f7fae429d80f630052ea8efb0cda4ef3ab5e3cda0e794559655/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6e6f6d6577616e672f4d33444d3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/fe50c0eebafab1a785f8061a847946cced6b96112f6013e52e9fef8d8a198a8b/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30303630312d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
CLIP is also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/a60771da0fe2c0fb2127e569c83d34ded72d62616b465ea9d20827fa446aa1e1/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6c696e7971323131372f434c49502d45533f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/b2dba067eb3956a2bfb2850b38b412e6430a717144510e58e7e7828050e13a32/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e30393530362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Weakly Supervised Semantic Segmentation via Adversarial Learning of Classifier and Reconstructor |
![GitHub](https://camo.githubusercontent.com/6dc348fc64b37a5545082ca97f04b2338305dbc9f5ea6b8e3cefcc0e1656d937/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f73616e67726f636b45472f4143523f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
➖ |
Conjugate Product Graphs for Globally Optimal 2D-3D Shape Matching |
![GitHub](https://camo.githubusercontent.com/17f88dfa906fc989ecb3e196f58df2d70c18355251ae10fe2b5774af9af6ef8a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7061756c306e6f61682f736d2d324433443f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/0b187a135f3cf0cbbef9f3c1351bf8531bd94cc8fb866045abb3ba056441f6a7/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231312e31313538392d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Interactive Segmentation of Radiance Fields |
![GitHub](https://camo.githubusercontent.com/cbaeaa2fc8202748b3cd4de980e1900faf84f6e87e5b06accfa5dd03b5dace42/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f726168756c2d676f656c2f697372665f636f64653f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/8ca18652c8c7e52c37102bb897153d661432d277744afe270e21513f6e908a9f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e31333534352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Boundary-Enhanced Co-Training for Weakly Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/ff837d19510770b5f0b904bf18d03f7829ed2136cd3cbfc6089e9c4c38c82372/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f5368656e67686169526f6e672f4245434f3f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Learning Multi-Modal Class-Specific Tokens for Weakly Supervised Dense Object Localization |
➖ |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
➖ |
Quantum Multi-Model Fitting ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/9631fbc1c51b76e8650d6d9324898d5ba05a1262097d634472c007c3c97d8919/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f466172696e614d617474656f2f716d6d663f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/65ba018ecc27d2ce92a55936f5da2f871218190be78a6da78bd03ee6dc5c1691/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31353434342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Two-Shot Video Object Segmentation |
![GitHub](https://camo.githubusercontent.com/f370741eca586ee628803ab35a574ef654a8b830678ffaf28dfbc4e6cd073918/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f796b2d706b752f54776f2d73686f742d566964656f2d4f626a6563742d5365676d656e746174696f6e3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/26c089bac52260d7f37c75583267b9efb65dfad70a0a09881abc09ee81e981e2/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31323037382d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
End-to-End Video Matting with Trimap Propagation |
![GitHub](https://camo.githubusercontent.com/2867e7dc38dde0bac37ae3cfec1efd90747e7510c4cc2013f318c673dbec2083/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6373767433323734352f4654502d564d3f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
ISBNet: A 3D Point Cloud Instance Segmentation Network with Instance-Aware Sampling and Box-Aware Dynamic Convolution |
![GitHub](https://camo.githubusercontent.com/802402973dbe1f5880c15dd4a2749f846bb5f1032cd934ec068662b32ee5cddf/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f56696e414952657365617263682f4953424e65743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/4419cd57d4ed81aca1dee503e097fad15171d987c44e45fd8973a8d205b61d04/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30303234362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
On Calibrating Semantic Segmentation Models: Analyses and an Algorithm |
![GitHub](https://camo.githubusercontent.com/a679dfdd5dfd8264800004e07eb34b9871a3e3bc9f18a697a970d4678fc1ed67/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6477616e673138312f73656c65637469766563616c3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/c6cf898f9090d504077cb444906a48e51ae6ca1a8aea48be6fa099271f1f2828/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e31323035332d6233316231622e737667) |
➖ |
Explicit Visual Prompting for Low-Level Structure Segmentations |
![GitHub](https://camo.githubusercontent.com/a0ccaef94c26df1684b611f34dfc79fbd14fd02d094960aac46cb59f4d9d26a7/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4e6946616e6742614147652f4578706c696369742d56697375616c2d50726f6d70743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/744251cb9e345e5fd430c543e5f5850411655cadc469a66f509c401152666162/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31303838332d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Neural Intrinsic Embedding for Non-Rigid Point Cloud Matching |
➖ |
![arXiv](https://camo.githubusercontent.com/8aa1e9819faf04c258fb86977d1930b87902ec1c5a84f08e6ff0a643b791c402/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30313033382d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Incrementer: Transformer for Class-Incremental Semantic Segmentation with Knowledge Distillation Focusing on Old Class ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
➖ |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Camouflaged Instance Segmentation via Explicit De-Camouflaging ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/8e38346904f47a2cf3951b8ff0babf764413e242e5a1b9af9a55012a47313adc/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f555354434c2f44434e65743f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Leveraging Hidden Positives for Unsupervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/3fd7110927c5a570c5c85970d45f6d19a88af3c5941465fec4cd1858a7dbf8d8/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f68796e6e736b2f48503f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/141850038f4311e7fcdea8075b2f1cd63ba14ab71e256177c39940c943c5643b/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31353031342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Rethinking the Correlation in Few-Shot Segmentation: A Buoys View |
![GitHub](https://camo.githubusercontent.com/965cbf94dae830b375b146a252ebb187e2f7e8645d19844948ecb7bf10870989/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6d726b73686c6c722f466577545552453f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Sparsely Annotated Semantic Segmentation with Adaptive Gaussian Mixtures |
![GitHub](https://camo.githubusercontent.com/2a0c7db8165027657f64ed83656cde28fb83c853bfe69f73649f73c2fce80be7/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4c7566667930332f41474d4d2d534153533f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Mask-Guided Matting in the Wild |
![GitHub](https://camo.githubusercontent.com/d74b64ef115d07fade28e6f75bd17313a35a01ef0fb23aa08d4e902395a86f59/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7975636f726e6574746f2f4d474d617474696e673f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention |
![GitHub](https://camo.githubusercontent.com/aa32a9396dcdac2e48ee123d26c11128dae26351cac0cc420319486c3aaedaa8/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f64696e676d79752f446570656e64656e63795669543f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/759a78991909ea526129dedcec1b770b2316cf3240a00528e27862e6d0ba438f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330342e30333238322d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Conflict-based Cross-View Consistency for Semi-Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/bf903bd6e680fac24644e597f54d7f78548ae18d3b6a5db8381b47d6e63cad36/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7869616f79616f333330322f434356433f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/be27eb049abddb5d36886f8f909716d9ab4a8dea5f51bb212a92528948024479/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30313237362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Augmentation Matters: A Simple-Yet-Effective Approach to Semi-Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/6b5768a10bcf85a8bb921084e9f7e7cf32d2cca780249836b0b66166e8985cb5/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f5a68656e5a48414f2f4175675365673f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/d481eeb2d6263748a632d518be24479f326131a7464d3a01fa22873bf1bb54a9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e30343937362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Attention-based Point Cloud Edge Sampling ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
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![arXiv](https://camo.githubusercontent.com/373b6560a1216a2ca12ca5ca1c847e151a7ef604528d11080d975c9140f5d8cd/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330322e31343637332d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
DA Wand: Distortion-Aware Selection using Neural Mesh Parameterization |
![GitHub](https://camo.githubusercontent.com/c0aba06a60486e2a2eb257a7217a74d84ed1bb875ab291c08775c67276dd7ac4/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7468726565646c652f44412d57616e643f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/9f706ae2046b3de1fb467b3154cddacc76553aa3322ae41bb31572d0544c1bbf/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231322e30363334342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Extracting Class Activation Maps from Non-Discriminative Features as Well |
![GitHub](https://camo.githubusercontent.com/2b455b4747ca616dd5580c3739ebceb7d180dc8e6f86e71d15dbfe3db793ab12/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7a68616f7a68656e674368656e2f4c5043414d3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/9a7403c2dd8f54ac674246f26d1d006b695546dd92c79bf216df6b13349db202/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31303333342d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Focused and Collaborative Feedback Integration for Interactive Image Segmentation |
![GitHub](https://camo.githubusercontent.com/89373646810b304dbaee35f3e3af1518c511908b231ca9ea09ac6836af3dbeb4/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f7665697a677961757a677961757a2f464346493f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/3b23a4f9725e245edeccdd4adeed8a9da162bb8fafba8690fadf823cafeb6f0c/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31313838302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Boosting Low-Data Instance Segmentation by Unsupervised Pre-Training with Saliency Prompt |
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![arXiv](https://camo.githubusercontent.com/601f2868de07820281354c8fde900baf5b0abeb6f63203215d42ce84a4fed60f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330322e30313137312d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Unsupervised 3D Shape Reconstruction by Part Retrieval and Assembly |
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![arXiv](https://camo.githubusercontent.com/ad91959609745e4a21654afc148f01213856917bacb4a1641bcce03048da9f81/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30313939392d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
MobileVOS: Real-Time Video Object Segmentation Contrastive Learning Meets Knowledge Distillation |
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![arXiv](https://camo.githubusercontent.com/ae8eee8ef8e3d8531a92a84c1bfd9e818d7e81d6ae7827828faccd1a20d18133/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e30373831352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Transformer Scale Gate for Semantic Segmentation |
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![arXiv](https://camo.githubusercontent.com/388dc1aeb8346fa4546cc9cd526db5b60651cf8aa6263a78fe936599f2074ad7/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323230352e30373035362d6233316231622e737667) |
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PIDNet: A Real-Time Semantic Segmentation Network Inspired by PID Controllers |
![GitHub](https://camo.githubusercontent.com/e36526f73f8a9b04aecd756262efe433c656236524741f8c5fa2af4375b6f1bb/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f58754a6961636f6e672f5049444e65743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/87f0e7b5dae5488b87636bda8cb1e92b062401a89a0293d6a51ad97414fec7fc/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323230362e30323036362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Side Adapter Network for Open-Vocabulary Semantic Segmentation ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
![GitHub](https://camo.githubusercontent.com/5cd5232f0be91afd789e900d3044f880b6ecac4119e800248293041364a897ab/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4d656e64656c58752f53414e3f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/e15192d7cb50f2184d04dca130328383c1a7f415c4ca6c8335e19e09482da893/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330322e31323234322d6233316231622e737667) |
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Test Time Adaptation with Regularized Loss for Weakly Supervised Salient Object Detection |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformers |
![GitHub](https://camo.githubusercontent.com/889637fc6131aab404e5c6392d80b6956b3c17ffab956496301186e6a028dd19/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f5a686f754875616e6732332f4653504e65743f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/e81147d6264f3a4eeb559e7464618218f1791809d682d7a018fce28e852855ce/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31343831362d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Reliability in Semantic Segmentation: Are we on the Right Track? |
![GitHub](https://camo.githubusercontent.com/5da7b6d7ad43210e7b941802d8e3337d09ac77cb363cb6fd9cc6efdd29325c0a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6e617665722f72656c69733f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/6f34c0703e84ff826fb5a7488b0242c70a06ebc8242352ca56c04b9934e11d34/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31313239382d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Beyond mAP: Towards Better Evaluation of Instance Segmentation ![CVPR - Highlight](https://camo.githubusercontent.com/5cb496e2b9e24dbb9469b9fdf6f120a9d249de14965ea65e1c41199f309ceac9/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f435650522d486967686c696768742d464646463030) |
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![arXiv](https://camo.githubusercontent.com/73bce0c8d42bcc99c55d7ad791ea1781a37e06dcef7af81d4c1e903dfe7ff3fa/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323230372e30313631342d6233316231622e737667) |
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Heat Diffusion based Multi-Scale and Geometric Structure-Aware Transformer for Mesh Segmentation |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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Tree Instance Segmentation with Temporal Contour Graph |
![GitHub](https://camo.githubusercontent.com/376ce6a7fbb15584eafdf88db37eeacb03737bd5242a9ddf2b64669b4efeaad9/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f61646e616e303831392f547265652d496e7374616e63652d5365676d656e746174696f6e2d7573696e672d54656d706f72616c2d537472756374757265642d496d616765733f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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Exemplar-FreeSOLO: Enhancing Unsupervised Instance Segmentation with Exemplars |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Omnimatte3D: Associating Objects and their Effects in Unconstrained Monocular Video |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Learning Orthogonal Prototypes for Generalized Few-Shot Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/747e62986481992f121558e1cb6e08fee1e9911f96bd4794bba1db57991d22a3/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6c7361313939372f504f503f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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Instance-Specific and Model-Adaptive Supervision for Semi-Supervised Semantic Segmentation |
![GitHub](https://camo.githubusercontent.com/91d714c1afd9468e678669475c181a142828bcd4ff3bc18e0ac62111c1deec72/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f5a68656e5a48414f2f694d41533f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/cdba8f5fd25a2a440f5d7ca0e6bff492ee9b005ae4fb17430101dfa7380044ed/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323231312e31313333352d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Improving Robustness of Semantic Segmentation to Motion-Blur using Class-Centric Augmentation |
![GitHub](https://camo.githubusercontent.com/f3f8efce53f0f47544367864346de0eee0b3cf4b7c6c0a223351fa12c59a8428/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f616b612d646973636f7665722f43434d42415f4356505232333f7374796c653d666c6174) |
![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
IFSeg: Image-Free Semantic Segmentation via Vision-Language Model |
![GitHub](https://camo.githubusercontent.com/0aec0fe358719582c3e3397b72a20a6c6b9499ce846ff8201cf7c7b2817d0fd5/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f616c696e6c61622f69667365673f7374796c653d666c6174) |
![arXiv](https://camo.githubusercontent.com/ff10eba06a410bcf9fcfb74e7d7f962a123caff68617001a59b3c648be52913e/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330332e31343339362d6233316231622e737667) |
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CLIP-S4: Language-Guided Self-Supervised Semantic Segmentation |
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![arXiv](https://camo.githubusercontent.com/8907cffb1048fd13c38ba2445b926aabce80c0b558137258f248aae9730fa2ac/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323330352e30313034302d6233316231622e737667) |
![YouTube](https://camo.githubusercontent.com/4c91b5d587f82e3ea0df6978845aea9370200c5f626a2fa7d6e48d2db40c8aa0/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f596f75547562652d2532334646303030302e7376673f7374796c653d666f722d7468652d6261646765266c6f676f3d596f7554756265266c6f676f436f6c6f723d7768697465) |
Pruning Parameterization with Bi-Level Optimization for Efficient Semantic Segmentation on the Edge |
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![thecvf](https://camo.githubusercontent.com/570147fbf0c4aade041dc1e76b9cc9cc802ebdef0c7e20c98df264ef7919b215/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7064662d7468656376662d3733393543352e737667) |
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