Stars
[MedIA] Paper list and source code for survey "A comprehensive survey on deep active learning in medical image analysis"
Project Page of 'GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction' [CVPR2019]
[CVPR 2023 Highlight] Perspective Fields for Single Image Camera Calibration
DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data (NeurIPS 2023 Spotlight) / / / / When Does Perceptual Alignment Benefit Vision Representations? (NeurIPS 2024)
A middleware library and sample application for high-quality skin and eye rendering
[SIGGRAPH Asia 2024] PuzzleAvatar: Assembling 3D Avatars from Personal Albums
Recent weakly supervised semantic segmentation paper
Enjoy the magic of Diffusion models!
End-to-end learning of deep visual representations for image retrieval
Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone
DeepLearning - Camelyon16 dataset
Large Language-and-Vision Assistant for Biomedicine, built towards multimodal GPT-4 level capabilities.
[ECCV 2024] Decomposition Betters Tracking Everything Everywhere
[ECCV2024] CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians
ECCV 2024 & GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes
Official implementation of DiffuseHigh, *Younghyun Kim, *Geunmin Hwang, Junyu Zhang, Eunbyung Park.
EMNLP'22 | MedCLIP: Contrastive Learning from Unpaired Medical Images and Texts
Official implementation for MedCLIP-SAMv2
Official implementation for MedCLIP-SAM (MICCAI 2024)
Code of Pyramidal Flow Matching for Efficient Video Generative Modeling
[ECCV 2024] This is the official code for the paper "Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations"
ACM Multimedia2020 University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization 🚁 annotates 1652 buildings in 72 universities around the world.
Official Pytorch implementation of MICCAI 2024 paper (early accept, top 11%) Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography