Learning to Curate What You Generate for Generalizable Few-Shot Class-Incremental Learning
cs.CV
Submitted: 2026-10-04
Updated: 2026-10-04
Comments: Accepted by ACM MM 2026
Code: https://github.com/NiHaoWoJiaoYYC/G-FSCIL
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- A Closer Look at Few-shot Classification
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
- LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs
- An Empirical Study of Example Forgetting during Deep Neural Network Learning
Related papers
- Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
- AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
- Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
- TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
- A Survey on Efficient Vision-Language-Action Models