Bi-Compatible Task-Agnostic Feature Augmentation for Expansion-Based Class-Incremental Learning
- 26 July 2026
- journal article
- research article
- Published by Springer Nature in International Journal of Computer Vision
- Vol. 134 (8) , 366
Abstract
No abstract availableKeywords
Funding Information
- Basic Research Program of Jiangsu Province (BK 20251251)
This publication has 64 references indexed in Scilit:
- Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You NeedInternational Journal of Computer Vision, 2024
- PyCIL: a Python toolbox for class-incremental learningScience China Information Sciences, 2023
- Visual Prompt Tuning2022
- DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning2022
- FOSTER: Feature Boosting and Compression for Class-Incremental Learning2022
- Topology-Preserving Class-Incremental Learning2020
- PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning2020
- Memory Aware Synapses: Learning What (not) to Forget2018
- Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence2018
- The Nature of Statistical Learning Theory2000