Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
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Updated
Sep 19, 2022 - Python
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
Official repository for "CLIP model is an Efficient Continual Learner".
Accelerating Vision-Language Pretraining with Free Language Modeling (CVPR 2023)
Bias-to-Text: Debiasing Unknown Visual Biases through Language Interpretation
[CVPR2023] The code for 《Position-guided Text Prompt for Vision-Language Pre-training》
A codebase for flexible and efficient Image Text Representation Alignment
PyTorch implementation of ICML 2023 paper "SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation"
Codes and Models for COSA: Concatenated Sample Pretrained Vision-Language Foundation Model
Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. [ICCV 2023 Oral]
Unofficial implementation for Sigmoid Loss for Language Image Pre-Training
📍 Official pytorch implementation of paper "ProtoCLIP: Prototypical Contrastive Language Image Pretraining" (IEEE TNNLS)
Recognize Any Regions
[NeurIPS 2023] Bootstrapping Vision-Language Learning with Decoupled Language Pre-training
Code for ACL 2023 Oral Paper: ManagerTower: Aggregating the Insights of Uni-Modal Experts for Vision-Language Representation Learning
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models
Demographic Bias of Vision-Language Foundation Models in Medical Imaging
DeepSeek-VL: Towards Real-World Vision-Language Understanding
FLAIR: A Foundation LAnguage-Image model of the Retina for fundus image understanding.
Codes and Models for VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
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