Synthetic Anomaly Generation

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Overview

Synthetic anomaly generation studies how to create abnormal examples for settings where real defects or rare events are limited, costly, or difficult to label. Common approaches use diffusion and other foundation models for text-, mask-, or reference-guided image editing, alongside procedural simulators, physics-based models, and latent-space pseudo-outlier generation for images, videos, time series, graphs, and 3D data. Synthetic examples support detector training and calibration, localization, and benchmarks with controllable anomaly types and labels. A central tension is balancing realism, diversity, and label accuracy with reliable transfer to real data, since synthetic artifacts or domain mismatch can undermine downstream performance.

Latest papers

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65 papers8 papers in the last four weeks, up 60% on the four weeks before. 0.0% of all new papers.

  1. Pos4CHD: A Positive-Free Mask-Guided Counterfactual Synthesis Framework for Fetal Congenital Heart Defect Analysis

    Oct 22, 2026Wenjie Xuan, Yapeng Li, Hang Su +5Medical Image SynthesisSynthetic Anomaly Generation

  2. Injection of Space Radiation Errors on Low-power NVM using Generative Deep Learning

    Oct 19, 2026Eleonora Giudici, Antonio Miele, Luca MottolaSynthetic Anomaly Generation

    Politecnico di Milano Milan, Italy · RISE and Uppsala University Uppsala, Sweden

  3. CORE: Contrast-and-Reflect for Self-Supervised Prompt Optimization in Anomaly Synthesis

    Oct 14, 2026Haoxiang Rao, Fang Zhao, Zhao Wang +3Synthetic Anomaly GenerationSynthetic Data Augmentation

    School of Intelligence Science and Technology, Nanjing University · China Mobile Zijin Innovation Institute

  4. Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies

    Oct 13, 2026Ufuk Efe, Alptekin TemizelAnomaly DetectionIndustrial Anomaly Detection

    Graduate School of Informatics, Middle East Technical University, Üniversiteler Mahallesi, Dumlupınar Bulvarı No:1, Ankara, 06800, Türkiye

  5. Is Real-World Training Data Necessary for Generalist Graph Anomaly Detection?

    Oct 8, 2026Yujing Liu, Yixin Liu, Yue Tan +4Anomaly DetectionGraph Foundation Models

    School of Information and Communication Technology, Griffith University, Australia · School of Computer Science and Technology, Tongji University, China

  6. Visual Anomaly Synthesis for Model Selection in Data Scarcity

    Sep 29, 2026Daniel Pröll, Thomas Kraxner, Tobias Schaefer +1Industrial Anomaly DetectionSynthetic Anomaly Generation

    Digital Factory Vorarlberg GmbH, Dornbirn, Austria · University of Salzburg, Salzburg, Austria · illwerke vkw AG, Bregenz, Austria +1

  7. FLASH: A "Generate Once, Synthesize Many" Framework for Synthetic Anomaly Generation in Industrial Anomaly Detection

    Sep 29, 2026Abhay Kumar Das, Rajesh Gangireddy, Ashwin Vaidya +1Synthetic Data AugmentationIndustrial Anomaly Detection

    Silicon University, Bhubaneswar, India · Intel

  8. Physics-Guided Conditional Diffusion Model for Rare Event Synthesis and Diagnosis for the Water-Gas Shift Reaction

    Sep 28, 2026Md Abrar Rafid Siddique, Bibek Aryal, Qiugang LuPhysics-Informed Generative ModelingSynthetic Anomaly Generation

    Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA

  9. Beyond Empirical Support: Structured Outlier Generation via Sinkhorn Optimal Transport

    Sep 25, 2026Haixiang Sun, Andrew L. LiuSynthetic Anomaly GenerationConstrained Generative Modeling

    Edwardson School of Industrial Engineering Purdue University West Lafayette, IN, 47906

  10. 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

  11. Score-based Outlier Generation via Controlling the Radon-Nikodym Derivative

    Sep 10, 2026Amartya Mukherjee, Tristan Milne, Kry Yik-Chau Lui +2Diffusion SamplingSynthetic Anomaly Generation

    Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1 · Royal Bank of Canada, 1 Place Ville Marie, Montreal, Quebec, H3C 3A9

  12. AnomalyCraft-700K: Component-Level Controllable and Verifiable Synthetic Anomalies for Fine-Grained Video Anomaly Understanding

    Sep 7, 2026Yuzhou Long, Haodong Zhang, Yunpeng Yang +2Synthetic Anomaly GenerationVideo Anomaly Detection

    Northwestern Polytechnical University · Singapore Management University

  13. DPA: Decoupling Product-Agnostic Anomaly Representations for Zero-shot Anomaly Generation

    Sep 2, 2026Hang Yao, Yansheng Fu, Ming Liu +4Industrial Anomaly DetectionDiffusion-Based Image Generation

  14. CAST: Context- and Anomaly Structure-Conditioned Time Series Anomaly Generation

    Aug 19, 2026Haochen Zhang, Jie Peng, Songyuan Sui +3Synthetic Anomaly GenerationTime Series Generation

    UNITES Lab, University of North Carolina at Chapel Hill · Rice University · Oregon State University

  15. DeCo: Zero-Shot Industrial Anomaly Generation through Decoupling and Recoupling

    Aug 8, 2026Shilei Zeng, Xurui Li, Yaohan Tang +1Industrial Anomaly DetectionSynthetic Anomaly Generation

    School of Electronic Information and Communications, Huazhong University of Science and Technology

  16. UniScale: Arbitrary-Scale Industrial Anomaly Generation

    Aug 8, 2026Shilei Zeng, Linxin Guan, Xurui Li +2Industrial Anomaly DetectionSynthetic Anomaly Generation

    School of Electronic Information and Communications, Huazhong University of Science and Technology

  17. OTLesMix: Wasserstein Barycenter and Optimal Transport Map for Synthetic Lesion Generation with Diverse Shapes and Locations

    Aug 6, 2026Robin Trombetta, Carole LartizienSynthetic Data AugmentationMedical Image Segmentation

    Univ. Lyon, CNRS UMR 5220, Inserm U1294, INSA Lyon, UCBL, CREATIS, France

  18. SynEnergy: Anomaly Semantic-Guided Diffusion for Synthetic Energy Data Generation

    Aug 4, 2026Lin Jiang, Dahai Yu, Ravikumar Gelli +1Synthetic Data GenerationTime Series Generation

    Department of Computer Science Florida State University Tallahassee, Florida, USA · Department of Electrical and Computer Engineering Florida State University Tallahassee, Florida, USA

  19. OSAGEN: Object-Aware Mask Priors and Multistage Decoupled Diffusion for Industrial Anomaly Generation

    Jul 31, 2026Jinyi Xu, Peng Chen, Yunkang Cao +3Industrial Anomaly DetectionAnomaly Localization

    School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University · School of Artificial Intelligence and Robotics, Hunan University · Department of Computer and Information Science, University of Macau +1

  20. Synthetic data generation framework for quality control automation in gravure printing

    Jul 23, 2026Korota Arsène Coulibaly, Mohamed Hamlich, Khalid Hmali +1Synthetic Data GenerationSynthetic Anomaly Generation

    LCCPS Lab, ENSAM, Hassan II University of Casablanca, 150 Bd du Nil, Casablanca, 20670, , Morocco · Plastima, Commune Chellalat, Route Secondaire 3002, Mohammedia, Casablanca, , , Morroco

  21. SAGA: Synthetic Agentic Graph Architecture for Temporal Benchmark Generation

    Jul 19, 2026Jiacheng Ding, Xiaofei ZhangSynthetic Data GenerationSynthetic Benchmark Generation

    University of Memphis · Memphis, Tennessee, USA · Tennessee

  22. 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

  23. Multi-Conditioned Diffusion Synthesis of Sand Boils for Low-Resource Earthen-Levee Inspection

    Jul 8, 2026Padam Jung Thapa, Abdullah Bin Naeem, Ayon Dey +2Synthetic Data AugmentationConditional Image Generation

    University of Louisiana at Lafayette, Lafayette, LA, USA · Department of Computer Science, Louisiana State University New Orleans, New Orleans, LA, USA

  24. Generative AI and Federated Learning for Intrusion Detection Systems: A Survey

    Jul 1, 2026Jiefei Liu, Abu Saleh Md Tayeen, Pratyay Kumar +5Network Intrusion DetectionSynthetic Anomaly Generation

    Department of Computer Science, New Mexico State University, Las Cruces, NM, USA · University of Hartford, CT, USA · DEVCOM Analysis Center, WSMR, NM, USA

  25. SENSE-VAD: Sentient and Semantic Video Anomaly Detection for Autonomous Driving

    Jun 30, 2026Nghia T. Nguyen, Lokman Bekit, Yasin YilmazAutonomous Driving BenchmarksVideo Anomaly Detection

    University of South Florida

  26. Redefining Maritime Anomaly Detection via Equation-Grounded Synthetic Anomalies

    Jun 29, 2026Youngseok Hwang, Sungho Bae, Dohun Lee +4Synthetic Anomaly GenerationTime-Series Anomaly Detection

    Seoul National University Seoul, Republic of Korea · KRISO Daejeon, Republic of Korea

  27. 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

  28. 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

  29. Mobility Anomaly Generation using LLM-Driven Behavior with Kinematic Constraints

    Jun 9, 2026Yueyang Liu, Joon-Seok Kim, Andreas ZüfleSynthetic Data GenerationSynthetic Anomaly Generation

    Emory University, Atlanta, USA

  30. TPA-AD: A Two-Stage Pseudo Anomaly-Guided Method for Bearing Time-Series Anomaly Detection

    Jun 2, 2026Xiancheng Wang, Zhibo Zhang, Ran Li +4Fault DetectionUnsupervised Anomaly Detection

    School of Ocean Engineering, Harbin Institute of Technology, West Wenhua Road, Weihai, 264209, Shandong, China · Technical Center, Bogie Development Department, CRRC Qingdao Sifang Locomotive and Rolling Stock Co., Ltd, Jinhong East Road, Qingdao, 266111, Shandong, China · Qingdao University, No. 308 Ningxia Road, Qingdao, 266071, Shandong, China