{"total":66,"rows":[{"id":"2404.06564","title":"MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection","created":"2024-04-09","cited_by_count":113,"area":"ssm"},{"id":"2405.14325","title":"Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection","created":"2024-05-23","cited_by_count":93,"area":null},{"id":"2503.06661","title":"AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP","created":"2025-03-09","cited_by_count":73,"area":null},{"id":"2503.02424","title":"Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection","created":"2025-03-04","cited_by_count":48,"area":null},{"id":"2311.02782","title":"Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead","created":"2023-11-05","cited_by_count":40,"area":null},{"id":"2410.14987","title":"SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning","created":"2024-10-19","cited_by_count":27,"area":null},{"id":"2403.09303","title":"Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective","created":"2024-03-14","cited_by_count":23,"area":null},{"id":"2406.01078","title":"Unseen Visual Anomaly Generation","created":"2024-06-03","cited_by_count":23,"area":null},{"id":"2505.01969","title":"MC3D-AD: A Unified Geometry-aware Reconstruction Model for Multi-category 3D Anomaly Detection","created":"2025-05-04","cited_by_count":23,"area":null},{"id":"2405.19882","title":"PixOOD: Pixel-Level Out-of-Distribution Detection","created":"2024-05-30","cited_by_count":20,"area":null},{"id":"2502.19848","title":"One-for-More: Continual Diffusion Model for Anomaly Detection","created":"2025-02-27","cited_by_count":19,"area":"diffusion"},{"id":"2402.18293","title":"Continuous Memory Representation for Anomaly Detection","created":"2024-02-28","cited_by_count":16,"area":null},{"id":"2505.07375","title":"Boosting Global-Local Feature Matching via Anomaly Synthesis for Multi-Class Point Cloud Anomaly Detection","created":"2025-05-12","cited_by_count":16,"area":null},{"id":"2403.20236","title":"Long-Tailed Anomaly Detection with Learnable Class Names","created":"2024-03-29","cited_by_count":14,"area":null},{"id":"2403.13015","title":"HyperVQ: MLR-based Vector Quantization in Hyperbolic Space","created":"2024-03-18","cited_by_count":13,"area":null},{"id":"2412.11802","title":"AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization","created":"2024-12-16","cited_by_count":12,"area":null},{"id":"2507.03903","title":"Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detection","created":"2025-07-05","cited_by_count":11,"area":null},{"id":"2510.00495","title":"Normal-Abnormal Guided Generalist Anomaly Detection","created":"2025-10-01","cited_by_count":10,"area":null},{"id":"2501.13864","title":"Autoencoders for Anomaly Detection are Unreliable","created":"2025-01-23","cited_by_count":9,"area":null},{"id":"2507.15905","title":"Foundation Models and Transformers for Anomaly Detection: A Survey","created":"2025-07-21","cited_by_count":8,"area":null},{"id":"2403.14213","title":"Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference","created":"2024-03-21","cited_by_count":7,"area":null},{"id":"2501.12295","title":"Towards Accurate Unified Anomaly Segmentation","created":"2025-01-21","cited_by_count":7,"area":null},{"id":"2506.03660","title":"INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning","created":"2025-06-04","cited_by_count":7,"area":null},{"id":"2506.21398","title":"FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection","created":"2025-06-26","cited_by_count":7,"area":null},{"id":"2510.17611","title":"Dinomaly2: A Unified Framework for Unsupervised Image Anomaly Detection","created":"2025-10-20","cited_by_count":6,"area":null},{"id":"2409.00942","title":"VQ-Flow: Taming Normalizing Flows for Multi-Class Anomaly Detection via Hierarchical Vector Quantization","created":"2024-09-02","cited_by_count":5,"area":null},{"id":"2411.16049","title":"ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift","created":"2024-11-25","cited_by_count":5,"area":null},{"id":"2504.02775","title":"TailedCore: Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly Detection","created":"2025-04-03","cited_by_count":5,"area":null},{"id":"2504.03306","title":"Multi-Flow: Multi-View-Enriched Normalizing Flows for Industrial Anomaly Detection","created":"2025-04-04","cited_by_count":5,"area":null},{"id":"2505.01476","title":"CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering","created":"2025-05-02","cited_by_count":5,"area":null},{"id":"2510.01934","title":"Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors","created":"2025-10-02","cited_by_count":5,"area":null},{"id":"2603.02629","title":"Towards an Incremental Unified Multimodal Anomaly Detection: Augmenting Multimodal Denoising From an Information Bottleneck Perspective","created":"2026-03-03","cited_by_count":4,"area":null},{"id":"2504.05662","title":"InvAD: Inversion-based Reconstruction-Free Anomaly Detection with Diffusion Models","created":"2025-04-08","cited_by_count":3,"area":"diffusion"},{"id":"2603.25159","title":"A Semantically Disentangled Unified Model for Multi-category 3D Anomaly Detection","created":"2026-03-26","cited_by_count":3,"area":null},{"id":"2404.00724","title":"Absolute-Unified Multi-Class Anomaly Detection via Class-Agnostic Distribution Alignment","created":"2024-03-31","cited_by_count":2,"area":null},{"id":"2412.00560","title":"Friend or Foe? Harnessing Controllable Overfitting for Anomaly Detection","created":"2024-11-30","cited_by_count":2,"area":null},{"id":"2503.21125","title":"Omni-AD: Learning to Reconstruct Global and Local Features for Multi-class Anomaly Detection","created":"2025-03-27","cited_by_count":2,"area":null},{"id":"2508.06588","title":"Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning","created":"2025-08-08","cited_by_count":2,"area":null},{"id":"2509.23741","title":"ResAD++: Towards Class Agnostic Anomaly Detection via Residual Feature Learning","created":"2025-09-28","cited_by_count":2,"area":null},{"id":"2601.22763","title":"Is Task-Specific Training Necessary for Anomaly Detection?","created":"2026-01-30","cited_by_count":2,"area":null},{"id":"2602.19611","title":"RAID: Retrieval-Augmented Anomaly Detection","created":"2026-02-23","cited_by_count":2,"area":"rag"},{"id":"2605.23070","title":"Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models","created":"2026-05-21","cited_by_count":2,"area":"diffusion"},{"id":"2507.16946","title":"Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts","created":"2025-07-22","cited_by_count":1,"area":null},{"id":"2508.02477","title":"Multi-class Image Anomaly Detection for Practical Applications: Requirements and Robust Solutions","created":"2025-08-04","cited_by_count":1,"area":null},{"id":"2508.17726","title":"Few-shot Human Action Anomaly Detection via a Unified Contrastive Learning Framework","created":"2025-08-25","cited_by_count":1,"area":null},{"id":"2511.22436","title":"ABounD: Adversarial Boundary-Driven Few-Shot Learning for Multi-Class Anomaly Detection","created":"2025-11-27","cited_by_count":1,"area":null},{"id":"2512.21264","title":"AnyAD: Unified Any-Modality Anomaly Detection in Incomplete Multi-Sequence MRI","created":"2025-12-24","cited_by_count":1,"area":null},{"id":"2605.26676","title":"Memory-Distilled Selection for Noise-Robust Anomaly Detection","created":"2026-05-26","cited_by_count":1,"area":null},{"id":"2406.15396","title":"Feature Purified Transformer With Cross-level Feature Guiding Decoder For Multi-class OOD and Anomaly Deteciton","created":"2024-04-30","cited_by_count":0,"area":null},{"id":"2407.04597","title":"Feature Attenuation of Defective Representation Can Resolve Incomplete Masking on Anomaly Detection","created":"2024-07-05","cited_by_count":0,"area":null},{"id":"2410.10234","title":"LADMIM: Logical Anomaly Detection with Masked Image Modeling in Discrete Latent Space","created":"2024-10-14","cited_by_count":0,"area":null},{"id":"2504.03442","title":"Pyramid-based Mamba Multi-class Unsupervised Anomaly Detection","created":"2025-04-04","cited_by_count":0,"area":"ssm"},{"id":"2506.02757","title":"Investigating Mask-aware Prototype Learning for Tabular Anomaly Detection","created":"2025-06-03","cited_by_count":0,"area":null},{"id":"2506.13097","title":"Pro-AD: Learning Comprehensive Prototypes with Prototype-based Constraint for Multi-class Unsupervised Anomaly Detection","created":"2025-06-16","cited_by_count":0,"area":null},{"id":"2508.16157","title":"Beyond Human-prompting: Adaptive Prompt Tuning with Semantic Alignment for Anomaly Detection","created":"2025-08-22","cited_by_count":0,"area":"mllm"},{"id":"2511.22595","title":"AnoRefiner: Anomaly-Aware Group-Wise Refinement for Zero-Shot Industrial Anomaly Detection","created":"2025-11-27","cited_by_count":0,"area":null},{"id":"2603.22861","title":"A Feature Shuffling and Restoration Strategy for Universal Unsupervised Anomaly Detection","created":"2026-03-24","cited_by_count":0,"area":null},{"id":"2604.08301","title":"GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2604.18393","title":"One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection","created":"2026-04-20","cited_by_count":0,"area":"diffusion"},{"id":"2605.02438","title":"Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection","created":"2026-05-04","cited_by_count":0,"area":"diffusion"},{"id":"2605.24402","title":"Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces","created":"2026-05-23","cited_by_count":0,"area":"diffusion"},{"id":"2607.12866","title":"Statistical Non-linear Reconstruction Loss for Image Anomaly Detection","created":"2026-07-14","cited_by_count":0,"area":null},{"id":"2608.05743","title":"ConceptADapt: Concept-guided Adaptive Feature Reconstruction with Dynamic Attention for Few-Shot Industrial Anomaly Detection","created":"2026-08-06","cited_by_count":0,"area":null},{"id":"2608.15277","title":"Memory-Bounded Continuation of Greedy Sampling for Continual Anomaly Detection","created":"2026-08-15","cited_by_count":0,"area":null},{"id":"2609.07229","title":"Proximity-CLIP: Text-Guided Semantic Proximity Learning for Zero-Shot Anomaly Detection","created":"2026-09-07","cited_by_count":0,"area":"mllm"},{"id":"2609.35059","title":"Towards Generalizable 3D Anomaly Detection via Relational Inconsistency Modeling","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}