Point Cloud Anomaly Detection

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Overview

Point cloud anomaly detection studies how to find and localize defects or unexpected structures in 3D scans, supporting quality inspection when failures are rare or costly to label. Common approaches compare local and global features with learned models of normal shapes, reconstruct clean geometry, or train with synthetic and physically plausible defects. Recent methods also use point-language models, image and depth fusion, and geometric or relational cues; they are evaluated on benchmarks such as MVTec 3D-AD, Real3D-AD, and Anomaly-ShapeNet. A central challenge is generalizing across object categories, sensors, and unseen defect types while balancing precise localization, limited anomaly data, and efficient inference.

Latest papers

CardsList

25 papers3 papers in the last four weeks, down 25% on the four weeks before. 0.0% of all new papers.

  1. Bidirectional Adaptive Transformers for Multimodal Anomaly Detection

    Oct 10, 2026Yuxin Jiang, Yunkang Cao, Weiming ShenMultimodal Anomaly DetectionMultimodal Fusion

    School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430000, Hubei, China

  2. Towards Generalizable 3D Anomaly Detection via Relational Inconsistency Modeling

    Sep 28, 2026KunHo Heo, SuYeon Kim, Hayoung Lee +2Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    Kyung Hee University

  3. Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection

    Sep 28, 2026Zhiqiang Qin, He Xie, Junfei Yi +5Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    School of Artificial Intelligence and Robotics, Hunan University · National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University

  4. AT3D-AD: Anomaly Type-Aware 3D Anomaly Detection via Hierarchical Point-Language Alignment

    Sep 22, 2026Jingyu Zeng, Haoquan Lu, Can GaoPoint Cloud Anomaly DetectionIndustrial Anomaly Detection

    College of Computer Science and Software Engineering and the Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China

  5. When Point Clouds Outperform Pixels: Rethinking Zero-Shot Multimodal Anomaly Detection

    Sep 22, 2026Chenglin Ye, Lupeng Liu, Dongbo Yu +2Multimodal Anomaly DetectionPoint Cloud Anomaly Detection

    School of Artificial Intelligence, University of Chinese Academy of Sciences

  6. PC2^2-AD: Point Cloud Upsampling to Safeguard 3D Anomaly Detection with Resolution-constrained Edge Devices

    Sep 13, 2026Yutong Gu, Yingxi Xie, Kejin Huang +4Point Cloud Anomaly DetectionAnomaly Detection

    Shenzhen University WeBank Institute of Finance, Shenzhen University, Shenzhen 518060, China · School of Computer Science, Wuhan University, Wuhan 430072, China · Shenzhen Audencia Financial Technology Institute, Shenzhen University, Shenzhen 518060, China +2

  7. Integrated Laser Scanning and Image-Based Topology Optimization Techniques for Detection and Quantification of Visible and Subsurface Structural Defects

    Sep 1, 2026Mehrdad Shafiei Dizaji, Devin HarrisPoint Cloud Anomaly DetectionModel Calibration

    Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, USA

  8. Damage Classification for 3D Point Cloud Data via 3D Data Analysis and Vision Foundation Model-based 2D Projections

    Aug 9, 2026Evan Perez, Kalelo Dukuray, Erika Ardiles-Cruz +1Point Cloud Anomaly DetectionVision Foundation Models

    Dept. of Computer Science, City College of New York, NY 10031, USA · Air Force Research Lab, Rome, NY 13441, USA

  9. Physics-inspired Pseudo Anomaly Generation and Prototype Feature Guidance for 3D Anomaly Detection

    Jul 12, 2026Jian Ning, Qin Zou, Linchun Wu +4Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    School of Computer Science, Wuhan University, Wuhan 430072, Hubei, China · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518060, Guangdong, China · School of Information and Software Engineering, East China Jiaotong University, Nanchang 330013, Jiangxi, China +1

  10. Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection

    Jun 28, 2026Ali Balapour, Faraz HachPoint Cloud Anomaly DetectionAnomaly Localization

    University of British Columbia, Vancouver, V6T 1Z4 BC, Canada · Vancouver Prostate Centre, M.H. Mohseni Institute of Urologic Sciences, Vancouver, V6H 3ZB BC, Canada · Department of Urologic Sciences, The University of British Columbia, Vancouver, V5Z 1M9 BC, Canada

  11. Point Cloud Diffusion with Global and Local Reconstruction for Instance-Level 3D Anomaly Detection

    Jun 24, 2026Linchun Wu, Qin Zou, Jiwen Lu +1Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    School of Computer Science, Wuhan University, Wuhan 430072, China · Department of Automation, Tsinghua University, Beijing 100084, China · Guangdong Artificial Intelligence and Digital Economy Laboratory (SZ), Shenzhen 518060, China

  12. VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment

    Jun 3, 2026Zi Wang, Katsuya Hotta, Yawen Zou +4Point Cloud Anomaly DetectionFew-Shot Anomaly Detection

    Niigata University, Niigata-city, Japan · Iwate University, Morioka, Japan · University of Toyama, Toyama-city, Japan

  13. Simultaneous Monitoring of Shape and Surface Color via 4D Point Clouds: A Registration-free Approach

    May 9, 2026Mariafrancesca Patalano, Giovanna Capizzi, Kamran PaynabarPoint Cloud Anomaly DetectionAnomaly Localization

    Department of Statistical Sciences, University of Padua · School of Industrial and Systems Engineering, Georgia Institute of Technology

  14. Two Steps Are All You Need: Efficient 3D Point Cloud Anomaly Detection with Consistency Models

    May 6, 2026Pranav A, Shashank B, Pranav Siddappa +3Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    1R.V. College of Engineering · 2Technical University of Applied Sciences Würzburg-Schweinfurt

  15. Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection

    May 5, 2026Haibo Xiao, Hanzhe Liang, Jie Zhou +2Point Cloud Anomaly DetectionSigned Distance Functions

    College of Computer Science and Software Engineering, Shenzhen University · Biological and Life Sciences Division, Mohamed bin Zayed University of Artificial Intelligence, UAE · Shenzhen Audencia Financial Technology Institute, Shenzhen University, China +1

  16. Breaking the Rigid Prior: Towards Articulated 3D Anomaly Detection

    Apr 29, 2026Jinye Gan, Bozhong Zheng, Xiaohao Xu +4Point Cloud Anomaly DetectionAnomaly Detection

    ShanghaiTech University · China · University of Michigan, Ann Arbor +1

  17. Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation

    Apr 26, 2026Simone Mosco, Daniel Fusaro, Alberto PrettoPoint Cloud Anomaly Detection3D Point Cloud Segmentation

    University of Padova, Italy

  18. Synthesis4AD: Synthetic Anomalies are All You Need for 3D Anomaly Detection

    Apr 6, 2026Yihan Sun, Yuqi Cheng, Junjie Zu +5Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    the National Center of Technology Innovation for Intelligent Design and Numerical Control, Huazhong University of Science and Technology, Wuhan 430074, China · the Department of Intelligent Manufacturing, Contemporary Amperex Technology Ltd., Ningde 352000, China · the Institute for Infocomm Research, A*STAR, Singapore 138632 +2

  19. Hierarchical Point-Patch Fusion with Adaptive Patch Codebook for 3D Shape Anomaly Detection

    Apr 5, 2026Xueyang Kang, Zizhao Li, Tian Lan +3Point Cloud Anomaly DetectionAnomaly Detection

    The University of Melbourne, Parkville, Victoria 3010, Australia · Tsinghua University, Haidian District, Beijing 100871, China · The University of New South Wales, Sydney, NSW 2052, Australia +1

  20. Open-Set Supervised 3D Anomaly Detection: An Industrial Dataset and a Generalisable Framework for Unknown Defects

    Apr 1, 2026Hanzhe Liang, Luocheng Zhang, Junyang Xia +7Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE · Shenzhen Audencia Financial Technology Institute, Shenzhen, China · School of Computer Science, Hangzhou Dianzi University, Hangzhou, China +4

  21. Ghost-FWL: A Large-Scale Full-Waveform LiDAR Dataset for Ghost Detection and Removal

    Mar 30, 2026Kazuma Ikeda, Ryosei Hara, Rokuto Nagata +6Point Cloud Anomaly Detection

    Keio University · Sony Semiconductor Solutions

  22. A Semantically Disentangled Unified Model for Multi-category 3D Anomaly Detection

    Mar 26, 2026SuYeon Kim, Wongyu Lee, MyeongAh ChoPoint Cloud Anomaly DetectionUnsupervised Anomaly Detection

    Kyung Hee University, Republic of Korea

  23. Multimodal Industrial Anomaly Detection via Geometric Prior

    Mar 24, 2026Min Li, Jinghui He, Gang Li +3Industrial Anomaly DetectionAnomaly Localization

    Faculty of Data Science, City University of Macau, Macau, China. · Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China. · Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing, Shandong Fundamental Research Center for Computer Science, Jinan, China.

  24. Back to Point: Exploring Point-Language Models for Zero-Shot 3D Anomaly Detection

    Mar 23, 2026Kaiqiang Li, Gang Li, Mingle Zhou +3Point Cloud Anomaly DetectionIndustrial Inspection

    Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China. · Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing, Shandong Fundamental Research Center for Computer Science, Jinan, China.

  25. GS-CLIP: Zero-shot 3D Anomaly Detection by Geometry-Aware Prompt and Synergistic View Representation Learning

    Feb 22, 2026Zehao Deng, An Liu, Yan WangZero-Shot Anomaly DetectionPoint Cloud Anomaly Detection

    School of Computer Science and Technology, Soochow University · Institute for AI Industry Research (AIR), Tsinghua University