1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces
Yaoxuan Feng, Yuxin Li, Weijiang Lv +5
Multi-class anomaly detection aims to build unified models across diverse product categories. However, as the number of categories grows, its performance often degrades due to incr…
Discovering Fine-Grained Visual-Concept Relations by Disentangled Optimal Transport Concept Bottleneck Models
Yan Xie, Zequn Zeng, Hao Zhang +5
Concept Bottleneck Models (CBMs) try to make the decision-making process transparent by exploring an intermediate concept space between the input image and the output prediction. E…
Explaining Domain Shifts in Language: Concept erasing for Interpretable Image Classification
Zequn Zeng, Yudi Su, Jianqiao Sun +6
Concept-based models can map black-box representations to human-understandable concepts, which makes the decision-making process more transparent and then allows users to understan…
Semantically Guided Dynamic Visual Prototype Refinement for Compositional Zero-Shot Learning
Zhong Peng, Yishi Xu, Gerong Wang +4
Compositional Zero-Shot Learning (CZSL) seeks to recognize unseen state-object pairs by recombining primitives learned from seen compositions. Despite recent progress with vision-l…