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Breaking the Rigid Prior: Towards Articulated 3D Anomaly Detection
Jinye Gan, Bozhong Zheng, Xiaohao Xu +4
Existing 3D anomaly detection methods are built on a rigid prior: normal geometry is pose-invariant and can be canonicalized through registration or alignment. This prior does not…
Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric Representation
Bozhong Zheng, Jinye Gan, Xiaohao Xu +5
3D point cloud anomaly detection is essential for robust vision systems but is challenged by pose variations and complex geometric anomalies. Existing patch-based methods often suf…
Towards Visual Discrimination and Reasoning of Real-World Physical Dynamics: Physics-Grounded Anomaly Detection
Wenqiao Li, Yao Gu, Xintao Chen +4
Humans detect real-world object anomalies by perceiving, interacting, and reasoning based on object-conditioned physical knowledge. The long-term goal of Industrial Anomaly Detecti…
Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties
Wenqiao Li, Bozhong Zheng, Xiaohao Xu +8
Object anomaly detection is essential for industrial quality inspection, yet traditional single-sensor methods face critical limitations. They fail to capture the wide range of ano…
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
Wenqiao Li, Xiaohao Xu, Yao Gu +3
Recently, 3D anomaly detection, a crucial problem involving fine-grained geometry discrimination, is getting more attention. However, the lack of abundant real 3D anomaly data limi…