VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix (ICML 2022)

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 VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset

Codes and Models for COSA: Concatenated Sample Pretrained Vision-Language Foundation Model

Evaluate robustness of adaptation methods on large vision-language models

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

This repository provides a comprehensive collection of research papers focused on multimodal representation learning, all of which have been cited and discussed in the survey just accepted https://dl.acm.org/doi/abs/10.1145/3617833 .

📍 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