Scholar
Hanzhe Liang
Google Scholar ID: pOL7KVkAAAAJ
ShenZhen University
3D Anomaly Detection
World Model
Mutimodel for Education
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Citations & Impact
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Citations
15
H-index
2
i10-index
0
Publications
6
Co-authors
8
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Publications
9 items
Open-Set Supervised 3D Anomaly Detection: An Industrial Dataset and a Generalisable Framework for Unknown Defects
2026
Cited
0
A Lightweight 3D Anomaly Detection Method with Rotationally Invariant Features
2025
Cited
0
IEC3D-AD: A 3D Dataset of Industrial Equipment Components for Unsupervised Point Cloud Anomaly Detection
2025
Cited
0
C3D-AD: Toward Continual 3D Anomaly Detection via Kernel Attention with Learnable Advisor
2025
Cited
0
Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detection
2025
Cited
0
Mentor3AD: Feature Reconstruction-based 3D Anomaly Detection via Multi-modality Mentor Learning
2025
Cited
0
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection
2025
Cited
0
Fence Theorem: Preprocessing is Dual-Objective Semantic Structure Isolator in 3D Anomaly Detection
2025
Cited
0
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Resume (English only)
Co-authors
8 total
Can Gao
Shenzhen University
Jinbao Wang
Assistant Professor, School of Artificial Intelligence, Shenzhen University
Tao Dai
Shenzhen University
Chengbin Hou
University of Birmingham
Guoyang Xie
Algorithm Manager, Department of Intelligent Manufacturing, CATL
Linlin Shen
Shenzhen University
Jie Zhang
Macao Polytechnic University
Aoran Wang
Shanghai AI Lab
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