10 citations · 14 across the 9 of their papers we have counts for
5 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…
One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection
Boan Zhang, Wen Li, Guanhua Yu +3
Diffusion models have achieved outstanding performance in unsupervised industrial anomaly detection (uIAD) by learning a manifold of normal data under the common assumption that of…
SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models
Weijiang Lv, Yaoxuan Feng, Xiaobo Xia +4
Chain-of-Thought reasoning is widely used to improve the interpretability of multimodal large language models (MLLMs), yet the faithfulness of the generated reasoning traces remain…
FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection
Long Tian, Yufei Li, Yuyang Dai +3
Few-shot industrial anomaly detection (FS-IAD) presents a critical challenge for practical automated inspection systems operating in data-scarce environments. While existing approa…
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…