133 citations · 469 across the 30 of their papers we have counts for
5 papers · 1 filter
Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Yunkang Cao, Xiaohao Xu, Chen Sun +2
Anomaly detection is a crucial task across different domains and data types. However, existing anomaly detection models are often designed for specific domains and modalities. This…
2nd Place Winning Solution for the CVPR2023 Visual Anomaly and Novelty Detection Challenge: Multimodal Prompting for Data-centric Anomaly Detection
Yunkang Cao, Xiaohao Xu, Chen Sun +3
This technical report introduces the winning solution of the team Segment Any Anomaly for the CVPR2023 Visual Anomaly and Novelty Detection (VAND) challenge. Going beyond uni-modal…
Segment Any Anomaly without Training via Hybrid Prompt Regularization
Yunkang Cao, Xiaohao Xu, Chen Sun +4
We present a novel framework, i.e., Segment Any Anomaly + (SAA+), for zero-shot anomaly segmentation with hybrid prompt regularization to improve the adaptability of modern foundat…
Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection
Yunkang Cao, Xiaohao Xu, Weiming Shen
Point cloud (PCD) anomaly detection steadily emerges as a promising research area. This study aims to improve PCD anomaly detection performance by combining handcrafted PCD descrip…
Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization
Yunkang Cao, Xiaohao Xu, Zhaoge Liu +1
Most unsupervised image anomaly localization methods suffer from overgeneralization because of the high generalization abilities of convolutional neural networks, leading to unreli…