Awesome Papers using PyCIL

Our Papers

• Class-Incremental Learning: A Survey (TPAMI 2024) [paper] [code]

• Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning (CVPR 2024) [paper] [code]

• Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning (ICML 2024) [paper] [code]

• Continual Learning with Pre-Trained Models: A Survey (IJCAI 2024) [paper] [code]

• Learning without Forgetting for Vision-Language Models (arXiv 2023) [paper]

• Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need (arXiv 2023) [paper] [code]

• PILOT: A Pre-Trained Model-Based Continual Learning Toolbox (arXiv 2023) [paper] [code]

• Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration (NeurIPS 2023) [paper] [Code]

• BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion (ICLR 2023) [paper] [code]

• A model or 603 exemplars: Towards memory-efficient class-incremental learning (ICLR 2023) [paper] [code]

• Few-shot class-incremental learning by sampling multi-phase tasks (TPAMI 2022) [paper] [code]

• Foster: Feature Boosting and Compression for Class-incremental Learning (ECCV 2022) [paper] [code]

• Forward compatible few-shot class-incremental learning (CVPR 2022) [paper] [code]

• Co-Transport for Class-Incremental Learning (ACM MM 2021) [paper] [code]

Other Awesome Works

• Towards Realistic Evaluation of Industrial Continual Learning Scenarios with an Emphasis on Energy Consumption and Computational Footprint (ICCV 2023) [paper] <https://openaccess.thecvf.com/content/ICCV2023/papers/Chavan_Towards_Realistic_Evaluation_of_Industrial_Continual_Learning_Scenarios_with_an_ICCV_2023_paper.pdf>`_`[code]

• Dynamic Residual Classifier for Class Incremental Learning (ICCV 2023) [paper] <https://openaccess.thecvf.com/content/ICCV2023/papers/Chen_Dynamic_Residual_Classifier_for_Class_Incremental_Learning_ICCV_2023_paper.pdf>`_`[code]

• S-Prompts Learning with Pre-trained Transformers: An Occam’s Razor for Domain Incremental Learning (NeurIPS 2022) [paper] <https://openreview.net/forum?id=ZVe_WeMold>`_`[code]