6 citations · 9 across the 9 of their papers we have counts for
9 papers
PASS++: A Dual Bias Reduction Framework for Non-Exemplar Class-Incremental Learning
Fei Zhu, Xu-Yao Zhang, Zhen Cheng +1
Class-incremental learning (CIL) aims to recognize new classes incrementally while maintaining the discriminability of old classes. Most existing CIL methods are exemplar-based, i.…
Unified Entropy Optimization for Open-Set Test-Time Adaptation
Zhengqing Gao, Xu-Yao Zhang, Cheng-Lin Liu
Test-time adaptation (TTA) aims at adapting a model pre-trained on the labeled source domain to the unlabeled target domain. Existing methods usually focus on improving TTA perform…
Ensemble Quadratic Assignment Network for Graph Matching
Haoru Tan, Chuang Wang, Sitong Wu +3
Graph matching is a commonly used technique in computer vision and pattern recognition. Recent data-driven approaches have improved the graph matching accuracy remarkably, whereas…
Active Generalized Category Discovery
Shijie Ma, Fei Zhu, Zhun Zhong +2
Generalized Category Discovery (GCD) is a pragmatic and challenging open-world task, which endeavors to cluster unlabeled samples from both novel and old classes, leveraging some l…
Revisiting Confidence Estimation: Towards Reliable Failure Prediction
Fei Zhu, Xu-Yao Zhang, Zhen Cheng +1
Reliable confidence estimation is a challenging yet fundamental requirement in many risk-sensitive applications. However, modern deep neural networks are often overconfident for th…
Towards Reliable Domain Generalization: A New Dataset and Evaluations
Jiao Zhang, Xu-Yao Zhang, Cheng-Lin Liu
There are ubiquitous distribution shifts in the real world. However, deep neural networks (DNNs) are easily biased towards the training set, which causes severe performance degrada…