Industrial Anomaly Detection

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Overview

Industrial anomaly detection aims to identify defects or unusual behavior when examples of failures are scarce and normal operation can vary across products, machines, and conditions. Visual methods often learn normal patterns with reconstruction models, patch-memory methods such as PatchCore, or pretrained vision features; synthetic defects and vision-language models are increasingly used to extend detection to new defect types. For sensor and audio data, common approaches include forecasting and reconstruction, autoencoders, and graph models that capture relationships among signals, with benchmarks such as MVTec AD, VisA, SWaT, and WADI. A central challenge is moving from strong results on curated benchmarks to reliable deployment under shifts, contaminated training data, tight false-alarm limits, and edge-device constraints.

Latest papers

CardsList

261 papers33 papers in the last four weeks, up 38% on the four weeks before. 0.2% of all new papers.

  1. ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing

    Jul 6, 2026Wei Sun, Weixia Zhang, Linhan Cao +30Industrial Anomaly DetectionIndustrial Inspection

    East China Normal University, Shanghai Jiao Tong University, Tsinghua Shenzhen International Graduate School, and Universit´e de Nantes.

  2. Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection

    Jul 4, 2026Runzhi Deng, Yundi Hu, Yiming Zhong +5Multimodal ICLIndustrial Anomaly Detection

    Nanjing University, Nanjing, Jiangsu, China · China Mobile Zijin Innovation Institute, Nanjing, Jiangsu, China · Southeast University, Nanjing, Jiangsu, China

  3. ArcAD: Anomaly-Rectified Calibration for Cold-Start Supervised Anomaly Detection

    Jul 2, 2026Ningning Han, Lei Fan, Jia Guo +5Industrial Anomaly DetectionReconstruction-Based Anomaly Detection

    Faculty of Computing, Harbin Institute of Technology, Harbin, China · University of New South Wales, Sydney, Australia · DZ-Matrix, Beijing, China +4

  4. LiZAD: A Lightweight Zero-Shot Anomaly Detection Framework for Industrial Manufacturing

    Jul 2, 2026Uzair Khan, Luigi Capogrosso, Muhammad Aqeel +3Edge InferenceIndustrial Anomaly Detection

    University of Verona · Interdisciplinary Transformation University of Austria · ETH Zurich

  5. GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models

    Jul 1, 2026Hongkuan Zhou, Tristan Rehm, Nadeem Nazer +3Industrial Anomaly DetectionVision-Language Grounding

    Corporate Research, Robert Bosch GmbH, Renningen, Germany · Institute for Artificial Intelligence University of Stuttgart, Stuttgart, Germany · Otto-von-Guericke-University Magdeburg, Magdeburg, Germany +1

  6. Detecting the Undetectable: Enhancing Unsupervised time series Anomaly Detection via Active Learning

    Jul 1, 2026Seung Hun Han, Hyeongwon Kang, Jinwoo Park +1Industrial Anomaly DetectionActive Learning

    LG CNS, 71 Magokjungang 8-ro, Gangseo-gu, Seoul, Republic of Korea · Department of Industrial & Management Engineering, Korea University, 126-16 Anam-dong 5-ga, Seongbuk-gu, Seoul, Republic of Korea · Department of Industrial Engineering, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul, Republic of Korea

  7. LogiCo: A Unified Framework for Logical and Structural Anomaly Detection

    Jun 27, 2026Ximiao Zhang, Min Xu, Xiuzhuang ZhouIndustrial Anomaly DetectionReconstruction-Based Anomaly Detection

    School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing, China · College of Information and Engineering, Capital Normal University, Beijing, China

  8. DeCoFlow: Structural Decomposition of Normalizing Flows for Continual Anomaly Detection

    Jun 25, 2026Hun Im, Jungi Lee, Subeen Cha +1Normalizing FlowsContinual Anomaly Detection

    Seoul National University, Seoul, Korea

  9. 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

  10. CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection

    Jun 24, 2026Ke Xu, Xinle Wang, Yanning Hou +3Industrial Anomaly DetectionMultimodal Anomaly Detection

    State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, Anhui University, Hefei, China · School of Artificial Intelligence, Anhui University, Hefei, China · College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China +1

  11. MATCH: Flow Matching for Multi-View Anomaly Detection

    Jun 23, 2026Mathis Kruse, Melissa Schween, Bodo RosenhahnIndustrial Anomaly DetectionAnomaly Localization

    Institute for Information Processing, L3S, Leibniz University Hannover, Germany

  12. Machine Learning Modeling for Real-Time Melt Pool Monitoring in Laser Powder Bed Fusion Additive Manufacturing: A Hybrid Approach

    Jun 22, 2026Inioluwa Emmanuel, Zhuo Yang, Ho Yeung +1Industrial Anomaly DetectionTransfer Learning

    Industrial and Manufacturing Engineering Florida State University Tallahassee, FL · National Institute of Standards and Technology Gaithersburg, Maryland

  13. UniSLAD: A Unified Framework for Structural and Logical Industrial Visual Anomaly Detection

    Jun 18, 2026Changyi Li, Chao Yang, Yu Xiao +1Industrial Anomaly DetectionAnomaly Detection

  14. DifferAD-R1: A Difference-Guided IndustrialAnomaly Localization with Multimodal LargeLanguage Models

    Jun 15, 2026Dingrong Wang, Xian Tao, Zhen Qu +5Reinforcement LearningIndustrial Anomaly Detection

    Institute of Automation, Chinese Academy of Sciences (CAS), Beijing 100190, China · School of Artificial Intelligence, University of Chinese Sciences, Beijing 100049, China · Institute of Automation, CAS, Beijing 100190, China +4

  15. Beer-Lambert Guided Representation Learning for Unsupervised Anomaly Detection in Sub-THz Food Inspection Images

    Jun 15, 2026Gyutae Hwang, Sang Jun LeeIndustrial Anomaly DetectionIndustrial Inspection

    Division of Electronics and Information Engineering, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju, 54896, Jeonbuk-do, Republic of Korea

  16. EdgeZSAD: Practical Zero-Shot Anomaly Detection on Edge Devices

    Jun 15, 2026Taewan Cho, Andrew Jaeyong ChoiEdge InferenceIndustrial Anomaly Detection

    1Gachon University · 2Plaid Labs Inc.

  17. Value-order Decomposition for Generalist Anomaly Detection

    Jun 12, 2026Miaoyun Zhao, Jing Chen, Miaoni Zhao +1Industrial Anomaly DetectionRepresentation Disentanglement

    Dalian University of Technology · Key Laboratory of Social Computing and Cognitive Intelligence (Dalian University of Technology), Ministry of Education, Dalian, China · Xi’an Chang’an Vanke City Primary School

  18. BoRAD: Bootstrap your Own Representations for Multi-class Anomaly Detection

    Jun 12, 2026Duy Hoang Khuong, Tri Nguyen Minh, Ngu Huynh Cong VietRepresentation LearningIndustrial Anomaly Detection

    Department of Artificial Intelligence FPT University Ho Chi Minh City, Vietnam · Department of IT FPT University Ho Chi Minh City, Vietnam · Department of Computing Fundamental FPT University Ho Chi Minh City, Vietnam

  19. Multi-Modal Agents for Power Distribution Defect Detection: An Evaluation of Foundation Models

    Jun 11, 2026Quan QuanIndustrial Anomaly DetectionMultimodal Reasoning

  20. Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline

    Jun 6, 2026Zekai Zhang, Qinghui Chen, Maomao Xiong +6VLM AdaptationIndustrial Anomaly Detection

    School of Control Science and Engineering, Shandong University, Jinan, China · National Supercomputing Center in Jinan, Qilu University of Technology, Jinan, China · College of Intelligence and Computing, Tianjin University, Tianjin, China +2

  21. Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselines

    Jun 6, 2026Zekai Zhang, Jinglin Zhang, Qinghui Chen +8Open-Vocabulary Object DetectionVLM Adaptation

    School of Control Science and Engineering, Shandong University, Jinan 250061, China · Shandong Computer Science Center, Qilu University of Technology, Jinan, China · CEREMADE, University Paris Dauphine, PSL Research University, CNRS, UMR 7534, 75775 Paris, France +4

  22. Anomaly Detection for Electro-Hydrostatic Actuators using LSTM Autoencoder

    Jun 3, 2026Nehal Afifi, Abdelmonem Elhendawi, Felix Leitenberger +2Industrial Anomaly DetectionReconstruction-Based Anomaly Detection

    IPEK - Institute of Product Engineering, Karlsruhe Institute of Technology (KIT), Germany. · SUPMICROTECH-ENSMM, France.

  23. Plan First, Judge Later, Run Better: A DMAIC-Inspired Agentic System for Industrial Anomaly Detection

    Jun 3, 2026Yongzi Yu, Ao Li, Le Wang +4Multi-Agent LLM SystemsLLM Agent Orchestration

    1The Hong Kong University of Science and Technology (Guangzhou) · 2The Hong Kong University of Science and Technology · 3Shanghai University of Finance and Economics +2

  24. Structure-Guided Mixed Masked Pretraining and Spatial Continuity Regularization for Printed Circuit Board Defect Detection

    Jun 2, 2026Peitong Wang, Nuo Wang, Enxin Qin +3Self-Supervised Pre-TrainingSmall Object Detection

    School of Big Data and Statistics, Anhui University, Hefei, 230601, China · School of Computer Science and Technology, Anhui University, Hefei, 230601, China · School of Artificial Intelligence and Data Science, University of Science and Technology of China, Hefei, 230026, China +1

  25. Normality-Preserving Continual Industrial Anomaly Detection via Orthogonal LoRA Banks

    Jun 1, 2026Weibai Fang, Haijun Che, Feiyang Ren +1Industrial Anomaly DetectionAnomaly Localization

  26. A Structured Benchmark for Text-Guided Anomaly Detection: When Language Stops Conditioning the Decision

    Jun 1, 2026Stefano Samele, Eugenio Lomurno, Teodora Jovanovic +3VLM EvaluationIndustrial Anomaly Detection

    Politecnico di Milano, AIRLab, Milan, Italy · S&H – Software & Hardware, Milan, Italy

  27. Contrastive Augmented Transformer with Domain-specific Enhancement for Robust Multi-scenario Metal Surface Defect Detection

    Jun 1, 2026Yiyao Liu, Wenxiao He, Liyuan Ren +1Contrastive LearningData Augmentation

    Glasgow College, University of Electronic Science and Technology of China, Chengdu, 611731, China · Institute of Applied Physics and Computational Mathematics, Beijing, China · Department of Industrial Engineering, Tsinghua University, Beijing, China

  28. IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems

    Jun 1, 2026Yuchen Zhang, Ning Xi, Pengbin Feng +5LLMs for CybersecurityReconstruction-Based Anomaly Detection

    School of Cyber Engineering, Xidian University, Xi’an 710126, China · School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia · School of Computer Science and Technology, Xidian University, Xi’an 710126, China

  29. Description and Discussion on DCASE 2026 Challenge Task 2: Noise-aware Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

    Jun 1, 2026Tomoya Nishida, Noboru Harada, Daiki Takeuchi +6Industrial Anomaly DetectionUnsupervised Anomaly Detection

    Hitachi, Ltd., Japan · NTT, Inc., Japan · SB Intuitions Corp. +1

  30. ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection

    May 31, 2026Uzair Khan, Luigi Capogrosso, Francesco Biondani +4Industrial Anomaly DetectionTime-Series Anomaly Detection

    University of Verona · Interdisciplinary Transformation University of Austria · ETH Zurich