133 citations · 469 across the 30 of their papers we have counts for
6 papers · 1 filter
Bidirectional Adaptive Transformers for Multimodal Anomaly Detection
Yuxin Jiang, Yunkang Cao, Weiming Shen
The effective integration of features derived from RGB images and 3D point clouds presents a substantial challenge in the field of multimodal anomaly detection (MAD). Existing MAD…
Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection
Zhiqiang Qin, He Xie, Junfei Yi +5
Existing 3D industrial anomaly detection mainly targets local geometric deviations. In contrast, many industrial anomalies violate object-level design or assembly rules, which we d…
ArcAD: Anomaly-Rectified Calibration for Cold-Start Supervised Anomaly Detection
Ningning Han, Lei Fan, Jia Guo +5
The deployment of Industrial Anomaly Detection (IAD) in real-world manufacturing frequently encounters a challenging cold-start bottleneck, in which limited normal samples fail to…
Synthesis4AD: Synthetic Anomalies are All You Need for 3D Anomaly Detection
Yihan Sun, Yuqi Cheng, Junjie Zu +5
Industrial 3D anomaly detection performance is fundamentally constrained by the scarcity and long-tailed distribution of abnormal samples. To address this challenge, we propose Syn…
URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
Wei Luo, Peng Xing, Yunkang Cao +3
Unsupervised anomaly detection plays a pivotal role in industrial defect inspection and medical image analysis, with most methods relying on the reconstruction framework. However,…
VTFusion: A Vision-Text Multimodal Fusion Network for Few-Shot Anomaly Detection
Yuxin Jiang, Yunkang Cao, Yuqi Cheng +2
Few-Shot Anomaly Detection (FSAD) has emerged as a critical paradigm for identifying irregularities using scarce normal references. While recent methods have integrated textual sem…