bjzhb666 / GS-LoRALinks
Practical Continual Forgetting for Pre-trained Vision Models (CVPR 2024; T-PAMI 2026)
☆70Updated last week
Alternatives and similar repositories for GS-LoRA
Users that are interested in GS-LoRA are comparing it to the libraries listed below
Sorting:
- [ECCV 2024] Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models☆56Updated last year
- [CVPR'24] Validation-free few-shot adaptation of CLIP, using a well-initialized Linear Probe (ZSLP) and class-adaptive constraints (CLAP)…☆80Updated 7 months ago
- CVPR2024: Dual Memory Networks: A Versatile Adaptation Approach for Vision-Language Models☆89Updated last year
- Official Pytorch implementation of "E2VPT: An Effective and Efficient Approach for Visual Prompt Tuning". (ICCV2023)☆72Updated 2 years ago
- [ICLR 2024] ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation☆71Updated last year
- Official Implementation of "Read-only Prompt Optimization for Vision-Language Few-shot Learning", ICCV 2023☆55Updated 2 years ago
- Task Residual for Tuning Vision-Language Models (CVPR 2023)☆75Updated 2 years ago
- [CVPR 2024] Offical implemention of the paper "DePT: Decoupled Prompt Tuning"☆109Updated last month
- 【ICCV 2023】Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning & 【IJCV 2025】Diffusion-Enhanced Test-time Adap…☆70Updated last year
- Generative Multi-modal Models are Good Class Incremental Learners, CVPR 2024 [PyTorch Code]☆49Updated last year
- [CVPR2024 Highlight] Official implementation for Transferable Visual Prompting. The paper "Exploring the Transferability of Visual Prompt…☆46Updated last year
- [CVPR 2023] Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners☆44Updated 2 years ago
- [CVPR2024] The code of "UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory"☆68Updated last year
- An official code for "Endpoints Weight Fusion for Class Incremental Semantic Segmentation"☆36Updated 2 years ago
- Exploring prompt tuning with pseudolabels for multiple modalities, learning settings, and training strategies.☆51Updated last year
- [ICCV2023] Borrowing Knowledge From Pre-trained Language Model: A New Data-efficient Visual Learning Paradigm☆19Updated 2 years ago
- Consistent Prompting for Rehearsal-Free Continual Learning [CVPR2024]☆36Updated 7 months ago
- Official repository for "CLIP model is an Efficient Continual Learner".☆108Updated 3 years ago
- Official implementation for paper "Knowledge Diffusion for Distillation", NeurIPS 2023☆94Updated last year
- [CVPR 2024] PriViLege: Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners☆55Updated last year
- [ICCV 2023 oral] This is the official repository for our paper: ''Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning''.☆75Updated 2 years ago
- [NeurIPS 2024] Code for Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models☆45Updated 10 months ago
- Official implementation of the paper "Masked Autoencoders are Efficient Class Incremental Learners"☆45Updated last year
- Official code for ICCV 2023 paper, "Improving Zero-Shot Generalization for CLIP with Synthesized Prompts"☆103Updated last year
- [NeurIPS 2023] Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization☆110Updated last year
- Distribution-Aware Prompt Tuning for Vision-Language Models (ICCV 2023)☆44Updated 2 years ago
- ☆34Updated 2 years ago
- LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections (NeurIPS 2023)☆29Updated 2 years ago
- ☆18Updated 2 years ago
- Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models☆106Updated last year