activity
20232026
most citedTowards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

cs.CV2025

Unsupervised Multi-View Visual Anomaly Detection via Progressive Homography-Guided Alignment

Xintao Chen, Xiaohao Xu, Bozhong Zheng +2

Unsupervised visual anomaly detection from multi-view images presents a significant challenge: distinguishing genuine defects from benign appearance variations caused by viewpoint…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2023★ 1 cited

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…