1 citations · 2 across the 9 of their papers we have counts for
4 papers · 2 filters
Sharpness-aware Dynamic Anchor Selection for Generalized Category Discovery
Zhimao Peng, Enguang Wang, Fei Yang +2
Generalized category discovery (GCD) is an important and challenging task in open-world learning. Specifically, given some labeled data of known classes, GCD aims to cluster unlabe…
Predictive Sample Assignment for Semantically Coherent Out-of-Distribution Detection
Zhimao Peng, Enguang Wang, Xialei Liu +1
Semantically coherent out-of-distribution detection (SCOOD) is a recently proposed realistic OOD detection setting: given labeled in-distribution (ID) data and mixed in-distributio…
Restoring Forgotten Knowledge in Non-Exemplar Class Incremental Learning through Test-Time Semantic Evolution
Haori Lu, Xusheng Cao, Linlan Huang +3
Continual learning aims to accumulate knowledge over a data stream while mitigating catastrophic forgetting. In Non-exemplar Class Incremental Learning (NECIL), forgetting arises d…
Learning Part Knowledge to Facilitate Category Understanding for Fine-Grained Generalized Category Discovery
Enguang Wang, Zhimao Peng, Zhengyuan Xie +3
Generalized Category Discovery (GCD) aims to classify unlabeled data containing both seen and novel categories. Although existing methods perform well on generic datasets, they str…