11 citations · 22 across the 3 of their papers we have counts for
6 papers
Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection
Hanzhe Liang, Guoyang Xie, Chengbin Hou +3
3D anomaly detection has recently become a significant focus in computer vision. Several advanced methods have achieved satisfying anomaly detection performance. However, they typi…
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning
Hongze Zhu, Guoyang Xie, Chengbin Hou +4
High-resolution point clouds~(HRPCD) anomaly detection~(AD) plays a critical role in precision machining and high-end equipment manufacturing. Despite considerable 3D-AD methods th…
Real3D-AD: A Dataset of Point Cloud Anomaly Detection
Jiaqi Liu, Guoyang Xie, Ruitao Chen +5
High-precision point cloud anomaly detection is the gold standard for identifying the defects of advancing machining and precision manufacturing. Despite some methodological advanc…
EasyNet: An Easy Network for 3D Industrial Anomaly Detection
Ruitao Chen, Guoyang Xie, Jiaqi Liu +4
3D anomaly detection is an emerging and vital computer vision task in industrial manufacturing (IM). Recently many advanced algorithms have been published, but most of them cannot…
K-Space-Aware Cross-Modality Score for Synthesized Neuroimage Quality Assessment
Guoyang Xie, Jinbao Wang, Yawen Huang +4
The problem of how to assess cross-modality medical image synthesis has been largely unexplored. The most used measures like PSNR and SSIM focus on analyzing the structural feature…
A Survey of Visual Sensory Anomaly Detection
Xi Jiang, Guoyang Xie, Jinbao Wang +4
Visual sensory anomaly detection (AD) is an essential problem in computer vision, which is gaining momentum recently thanks to the development of AI for good. Compared with semanti…