ABD:paper(Always be dreaming: A new approach for data-free class-incremental learning) SCR:paper(Supervised contrastive replay: Revisiting the nearest class mean classifier in online class-incremental continual learning) S&B:paper(Split-and-Bridge: Adaptable Class Incremental Learning within a Single Ne...
[2025-03]🌟 Check out our latest work on class-incremental learning (CVPR 2025)! [2025-02]🌟 Check out our latest work on pre-trained model-based domain-incremental learning (CVPR 2025)! [2025-02]🌟 Check out our latest work on class-incremental learning with vision-language models ...
Incremental learning has been proposed to retain the knowledge of old classes while learning to identify new classes. A typical approach is to use a few exemplars to avoid forgetting old knowledge. In such a scenario, data imbalance between old and new classes is a key issue that leads to ...
WuYichen-97/SD-Lora-CL: [ICLR 2025 Oral ] SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learninggithub.com/WuYichen-97/SD-Lora-CL 简述 基础模型在持续学习中表现出色,可高效迁移知识并抗灾难性遗忘。一种常用方法是调整其 Prompt 适应新任务,比如 L2P、DualPrompt、CODA-Pro...
class-incremental learning Class Incremental Learning Incremental Learning Relation Datasets Edit ImageNet CIFAR-100 Results from the Paper Edit Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers. Methods...
btw这篇文章里面continual learning和incremental learning这两个名次有些混用,如果有疑惑我觉得这个讨论可以看看github.com/xialeiliu/Aw 问题定义 在连续学习中有多个sequential task,然后每个task可能都有多个训练数据,连续学习的目标就是使得模型在当前任务以及之前所有任务上的表现都能最有。由于本文针对class CL进行研...
Results show that Ad- visIL has better overall performance than any of the in- dividual combinations of a learning algorithm and a neu- ral architecture. AdvisIL's code is available at https: //github.com/EvaJF/AdvisIL. 1. Introduction Practical applications of artificial intelligence often...
while ensuring fast inference. We conduct experiments in common benchmarks and demonstrate that our MULTI-LANE achieves a new state-of-the-art in MLCIL. Additionally, we show that MULTI-LANE is also competitive in the CIL setting. Source code available at https://github.com/tdemin16/multi-...
It also scales up to the largest problem size ever tried in this few-shot setting by learning 423 novel classes on top of 1200 base classes with less than 1.6% accuracy drop. Our code is available at https://github.com/ IBM/constrained-FSCIL. 1. Introduction Deep convolutional neural ...
Code is available at https://github.com/wqzh/BEDM. Introduction Deep learning has exhibited remarkable performance in various fields over the past decade, including computer vision (He et al., 2016, Wang, Bochkovskiy, and Liao, 2023), natural language processing (Roh et al., 2021, ...