Anomaly Localization

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15 papers in the last four weeks, up 114% on the four weeks before. 0.1% of all new papers.

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Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding?
Oct 8, 2026Xingwu Zhang, Duanyang Du, Huiling Zhu +5Industrial Anomaly Detection Multimodal Anomaly Detection
Hunan University · University of Aberdeen · South China Normal University +1
MIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI
Oct 1, 2026Negin Kafee Hernashki, Soumick ChatterjeeAnomaly Localization Unsupervised Anomaly Detection
Università degli Studi di Milano, Milan, Italy · Politecnico di Milano, Milan, Italy · Human Technopole, Milan, Italy +1
Anomaly Detection and Localization for the Pantograph-Catenary System
Oct 1, 2026Francesco Vitale, Hangli Ge, Francesco FlamminiIndustrial Anomaly Detection Anomaly Localization
DIETI University of Naples Federico II Naples, Italy · Interfaculty Initiative in Information Studies The University of Tokyo Tokyo, Japan · DIMAI University of Florence Florence, Italy +1
Detect, Explain, Interpret: An End-to-End Benchmark for Time Series Anomaly Detection, Explainability and Interpretability
Oct 1, 2026Roberto Stanzione, Jules Barbe, Magali Parrino +2Interpretable Anomaly Detection Anomaly Localization
Inria, ENS, CNRS, PSL Paris, France · Scality Paris, France · Inria, ENS, CNRS, PSL, EDF Paris, France
PCB-MC: Missing Component Analysis in Printed Circuit Boards
Sep 30, 2026Betsy Villa Brochero, Ian Gibson, Estefania TalaveraIndustrial Inspection Anomaly Localization
EEMCS-CS-DMB University of Twente Enschede, The Netherlands · ET-DPM-AMSPES University of Twente Enschede, The Netherlands
TED:Text-Axis Evidence Decomposition for Prompted Anomaly Localization
Sep 30, 2026JinYoung Kim, Geonho Kim, GiJeong Park +2Domain Generalization Anomaly Localization
Department of Artificial Intelligence, Chung-Ang University, Seoul, Korea · SNUAILAB Co., Ltd., Seoul, Korea
LEARN-TS: LLM-Enhanced Alignment and Reconstruction with Normality Guidance for Multivariate Time-Series Anomaly Detection
Sep 30, 2026Jahyeob Koo, Kio Yun, Byoungmo Koo +1Anomaly Localization Reconstruction-Based Anomaly Detection
Department of Industrial and Management Engineering, Korea University Seoul, Republic of Korea
Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection
Sep 28, 2026Zhiqiang Qin, He Xie, Junfei Yi +5Point Cloud Anomaly Detection Industrial Anomaly Detection
School of Artificial Intelligence and Robotics, Hunan University · National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University
Industrial Anomaly Detection via Defect-Grounded Reasoning in Visual Latent Space
Sep 24, 2026Jaron Yeh, Yen-Wei Chang, Jiang Liu +1Industrial Anomaly Detection Anomaly Localization
National Taiwan University · AMD GenAI
Unsupervised Brain Anomaly Detection as a Bayesian Inverse Problem with Diffusion Prior
Sep 21, 2026Hugues Roy, Reuben Dorent, Ninon BurgosMedical Image Anomaly Detection Anomaly Localization
Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
SAFe: Segment-guided Aggregation of Feature Densities for Anomaly-aware Segmentation
Sep 21, 2026Anja Delić, Jurica Runtas, Marin Oršić +2Anomaly Localization Density Estimation
University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Zagreb, Croatia
Earth Surface Immune System for Rapid Monitoring of Unknown Anomalies
Sep 17, 2026Jingtao Li, Qian Zhu, Xinyu Wang +3Remote Sensing Change Detection Anomaly Localization
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, P. R. China. · School of Remote Sensing and Information Engineering, Wuhan University, P. R. China.
A Non-Linear Neuron Based Detection of Isolated Pixels in Binary and Grayscale Images using Contrast Sensitive Receptive Fields
Sep 16, 2026Nassir MohammadAnomaly Localization
Cyber Innovation Lab, VCX, Airbus, Newport, UK
PSMP-CLIP: Patch-Prompt SAM and Multi-Semantic Prompting for CLIP-Based Zero-Shot Anomaly Detection
Sep 15, 2026Xuezhi Xiang, Guanghao Wu, Heqi Xiang +4Promptable Image Segmentation Anomaly Localization
Information and Communication Engineering, Harbin Engineering University, Harbin, China · Key Laboratory of Advanced Marine Communication and Information Technology, Harbin, China · Department of Computer Science, University of Toronto, Toronto, ON M5S 2E4, Canada +1
SIM: Subspace Interaction-based Method for Token-Level Text Anomaly Detection
Sep 8, 2026Kehan Yan, Yue Tan, Qingfeng Chen +3Anomaly Localization Anomaly Detection
Guangxi University, Guangxi, China · Griffith University, Queensland, Australia
Proximity-CLIP: Text-Guided Semantic Proximity Learning for Zero-Shot Anomaly Detection
Sep 7, 2026Manwen Yang, Leqian Ding, Yu Guo +1VLM Adaptation Anomaly Localization
School of Software Engineering, Xi’an Jiaotong University · State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University
PL-SCEA: Reconfiguring Pretrained Attention for Few-Shot Industrial Anomaly Detection
Sep 3, 2026Xiaoyu Yang, Qixing Wu, Huixian Zhao +1Few-Shot Anomaly Detection Vision Foundation Model Adaptation
School of Airspace Science and Engineering, Shandong University, Shandong, China
Neural-Collapse-guided Task-Free Continual Anomaly Detection
Sep 3, 2026Xiaotong Kong, Chaoyang Song, Ziai Zhou +3Continual Learning Industrial Anomaly Detection
Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing 210096, China
Fine-Grained Anomaly Perception in Wild UGC-Enhanced Images: A Comprehensive Dataset and Difference-Fusion Framework
Sep 2, 2026Yan Zhong, Gefei Chen, Qiufang Ma +4Anomaly Localization Image Quality Assessment
Peking University, Beijing, China · Douyin, ByteDance Inc. · Communication University of China, Beijing, China
SynCrash: A Multi-Stage Pipeline for Zero-Shot Accident Detection and Localization in Traffic Surveillance Video
Aug 30, 2026Arkya Jyoti Bagchi, Ritul Jangir, Varun RaskarTraffic Accident Anticipation Anomaly Localization
Indian Institute of Technology Jodhpur, India
Verifiable abstention makes AI leak diagnosis accountable in urban water distribution networks
Aug 19, 2026Tianwei Mu, Yue Wang, Mingzhe Yuan +8Selective Prediction Anomaly Localization
School of Municipal Engineering and Environment, Shenyang Jianzhu University, Shenyang 110168, China. · Guangzhou Institute of Industrial Intelligence, Guangzhou 510000, China. · Key Laboratory of Ecological Restoration of Regional Contaminated Environment, Ministry of Education, College of Environment, Shenyang University, Shenyang 110044, China. +3
Localizing to Debias: A Patch-Level Benchmark and Baseline for Weakly Supervised Spatial Anomaly Detection
Aug 12, 2026Sara Abdulaziz, Abdulrahman Al-Abri, Giacomo D'Amicantonio +1Anomaly Localization Weakly Supervised Video Anomaly Detection
Eindhoven University of Technology, 5612 AE Eindhoven, Netherlands
Beyond Hazard Resemblance: Contrastive Event Adjudication for Training-Free Video Anomaly Detection
Aug 10, 2026Wenti Yin, Xiang Wang, Huaxin Zhang +4Interpretable Anomaly Detection Anomaly Localization
Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology · Alibaba Group · The Hong Kong University of Science and Technology (Guangzhou)
Glance, Scrutinize, and Think: Advancing Video Anomaly Detection from Training-Free to Agentic Reasoning
Aug 7, 2026Shibo Gao, Peipei Yang, Xu-Yao Zhang +1Anomaly Localization Video Anomaly Detection
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China. · Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. · State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
ConceptADapt: Concept-guided Adaptive Feature Reconstruction with Dynamic Attention for Few-Shot Industrial Anomaly Detection
Aug 6, 2026Yufei Li, Yicheng Ruan, Long Tian +2Few-Shot Anomaly Detection Industrial Anomaly Detection
School of Computer Science and Technology, Xidian University, Xi’an, China
TAU-Bench: From Anomaly Instance Tracking to Fine-Grained Video Anomaly Understanding
Aug 6, 2026Kepeng Yang, Dongxuan Liu, Rongxin Gao +8VLM Evaluation Anomaly Localization
XMU · THU · CUHK +1
Grounded Well-Condition Anomaly Detection on the Volve Field: Constructed Labels, a Baseline, and a Dual-Head Model
Aug 6, 2026Gospel Bassey, Samuel Bassey, Vincent FakiyesiIndustrial Anomaly Detection Fault Detection
Independent Researcher. · College of Engineering, Biochemical Engineering. University of Georgia. · College of Engineering, EETI. University of Georgia.
Innovation-Residual Auditing of Autonomous Analysis Agents: Localization, Detection Limits, Error Control, and Identifiability
Aug 6, 2026Ahmed Hassoon, Mark DredzeAlgorithmic Auditing FDR Control
Johns Hopkins University
PADFormer: Pose-agnostic Anomaly Detection from Sparse View Images
Aug 4, 2026Ruiqi Wang, Yiming Qian, Fenggen Yu +4Few-Shot Anomaly Detection Anomaly Localization
Amazon · Simon Fraser University · ⋆Work carried out during internship at Amazon. +1
Keep the Needle, Prune the Haystack: Defect-Preserving Token Pruning for Efficient Zero-Shot Anomaly Detection
Aug 4, 2026Yanning Hou, Jingyuan Zhang, Xiaoyun Wang +3Medical Image Anomaly Detection Industrial Anomaly Detection
2National University of Defense Technology, Changsha, China · 1Anhui University, Hefei, China

Oct 8, 2026, cs.CVJ/K move · Enter open · S save

Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding?

Xingwu Zhang, Duanyang Du, Huiling Zhu, Jiayue Dai+4

Hunan University · University of Aberdeen · South China Normal University+1

Industrial Anomaly Detection Multimodal Anomaly Detection Anomaly Localization Multi-Agent LLMs

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A single multimodal large language model (MLLM) struggles to excel simultaneously at detection, localization, description, and reasoning in multimodal industrial anomaly understanding (MM-IAU). We show that in-domain training does not close this gap. On MMAD, a widely adopted MM-IAU benchmark, trained specialists reach at most 75.5% accuracy in defect localization, against 92.3% for human experts, and even detect anomalies less accurately than their untrained base model. Meanwhile, different MLLMs offer complementary strengths but share this weakness in fine-grained perception, so combining them alone cannot remove it. We therefore propose SiGMA, a spatially grounded multi-agent framework that divides labor between heterogeneous MLLM agents and a dedicated visual defect expert. A multimodal searcher supplies industrial knowledge and normal references, the defect expert turns query-reference comparison into calibrated anomaly evidence, and a label-free reliability controller weighs each source by task-wise competence and query-level evidence quality. SiGMA reaches 85.2% average accuracy on MMAD, 4.0% above the strongest trained specialist and Gemini-2.5-Pro and within 1.5% of human experts. Even with three agents of at most 9B parameters, it reaches 84.4%, and new MLLMs join without retraining.

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