tim-learn / UEOLinks
ICML-2024 highlight paper "Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization"
☆18Updated last year
Alternatives and similar repositories for UEO
Users that are interested in UEO are comparing it to the libraries listed below
Sorting:
- [ICML 2024] Offical code repo for ICML2024 paper "Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with …☆31Updated last year
- [CVPR 2024] Official Repository for "Efficient Test-Time Adaptation of Vision-Language Models"☆112Updated last year
- [NeurIPS 2025 Datasets & Benchmarks Track] The Illusion of Progress? A Critical Look at Test-Time Adaptation for Vision-Language Models☆30Updated 2 months ago
- ☆22Updated last month
- About Code Release for "CLIPood: Generalizing CLIP to Out-of-Distributions" (ICML 2023), https://arxiv.org/abs/2302.00864☆69Updated 2 years ago
- CVPR 2025 - R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning☆18Updated 4 months ago
- Official code for ICML 2024 paper, "Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models"☆19Updated last year
- [ICML 2025] DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation☆24Updated 2 months ago
- Official implementations of our LaZSL (ICCV'25)☆38Updated 6 months ago
- The official implementation of CVPR 24' Paper "Learning Transferable Negative Prompts for Out-of-Distribution Detection"☆60Updated last year
- ☆35Updated 2 years ago
- [NeurIPS 2024] Code for Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models☆45Updated 10 months ago
- Official code for ICCV 2023 paper, "Improving Zero-Shot Generalization for CLIP with Synthesized Prompts"☆103Updated last year
- [ICLR 2025] "Noisy Test-Time Adaptation in Vision-Language Models"☆12Updated 10 months ago
- Official code for ICLR 2024 paper, "A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation"☆85Updated last year
- Adaptation of vision-language models (CLIP) to downstream tasks using local and global prompts.☆50Updated 6 months ago
- PyTorch Implementation for InMaP☆11Updated 2 years ago
- [AAAI 2024] Prompt-based Distribution Alignment for Unsupervised Domain Adaptation☆74Updated last year
- Code for our NeurIPS 2022 (spotlight) paper 'Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation'☆73Updated last year
- The Pytorch implementation of Domain-Agnostic Mutual Prompting for Unsupervised Domain Adaptation☆37Updated last year
- ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection☆26Updated last year
- Pytorch implementation of DAPrompt: https://arxiv.org/abs/2202.06687☆96Updated 2 years ago
- [ICLR 2024 Spotlight] "Negative Label Guided OOD Detection with Pretrained Vision-Language Models"☆29Updated last year
- Exploring prompt tuning with pseudolabels for multiple modalities, learning settings, and training strategies.☆51Updated last year
- ☆55Updated last year
- This repository provides the official implementation for Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain …☆34Updated 3 years ago
- Official implementation of Few-shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt (ECCV2024)☆34Updated last year
- 🔥MDCS: More Diverse Experts with Consistency Self-distillation for Long-tailed Recognition [Official, ICCV 2023]☆30Updated last year
- Code for NeurIPS 2022 paper “S-Prompts Learning with Pre-trained Transformers: An Occam’s Razor for Domain Incremental Learning“☆106Updated last year
- [NeurIPS 2024] WATT: Weight Average Test-Time Adaptation of CLIP☆56Updated last year