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"
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
📍 Official pytorch implementation of paper "ProtoCLIP: Prototypical Contrastive Language Image Pretraining" (IEEE TNNLS)
[NeurIPS 2023] Bootstrapping Vision-Language Learning with Decoupled Language Pre-training
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models
DeepSeek-VL: Towards Real-World Vision-Language Understanding
[EMNLP 2023 Demo] Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
Easy wrapper for inserting LoRA layers in CLIP.
Multi-Aspect Vision Language Pretraining - CVPR2024
LAVIS - A One-stop Library for Language-Vision Intelligence
Recognize Any Regions
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