{"total":160,"rows":[{"id":"2110.11334","title":"Generalized Out-of-Distribution Detection: A Survey","created":"2021-10-21","cited_by_count":802,"area":null},{"id":"2101.10030","title":"Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning","created":"2021-01-25","cited_by_count":230,"area":null},{"id":"2104.01633","title":"MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection","created":"2021-04-04","cited_by_count":138,"area":null},{"id":"2203.03962","title":"Generative Cooperative Learning for Unsupervised Video Anomaly Detection","created":"2022-03-08","cited_by_count":102,"area":null},{"id":"2111.08644","title":"UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection","created":"2021-11-16","cited_by_count":93,"area":null},{"id":"2302.05160","title":"Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection","created":"2023-02-10","cited_by_count":90,"area":null},{"id":"2211.15098","title":"MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly Detection","created":"2022-11-28","cited_by_count":89,"area":null},{"id":"2404.01014","title":"Harnessing Large Language Models for Training-free Video Anomaly Detection","created":"2024-04-01","cited_by_count":87,"area":null},{"id":"2104.06689","title":"Learning Normal Dynamics in Videos with Meta Prototype Network","created":"2021-04-14","cited_by_count":71,"area":null},{"id":"2212.05136","title":"CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly Detection","created":"2022-12-09","cited_by_count":67,"area":null},{"id":"2303.12369","title":"Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection","created":"2023-03-22","cited_by_count":64,"area":null},{"id":"2302.05087","title":"Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Models","created":"2023-02-10","cited_by_count":59,"area":null},{"id":"2311.07042","title":"Open-Vocabulary Video Anomaly Detection","created":"2023-11-13","cited_by_count":57,"area":null},{"id":"2404.08531","title":"Text Prompt with Normality Guidance for Weakly Supervised Video Anomaly Detection","created":"2024-04-12","cited_by_count":49,"area":null},{"id":"2212.04090","title":"Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection","created":"2022-12-08","cited_by_count":47,"area":null},{"id":"2401.05702","title":"Video Anomaly Detection and Explanation via Large Language Models","created":"2024-01-11","cited_by_count":47,"area":null},{"id":"2104.07268","title":"Weakly Supervised Video Anomaly Detection via Center-guided Discriminative Learning","created":"2021-04-15","cited_by_count":44,"area":null},{"id":"2306.14451","title":"Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly Detection","created":"2023-06-26","cited_by_count":43,"area":null},{"id":"2408.05905","title":"Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts","created":"2024-08-12","cited_by_count":40,"area":null},{"id":"2303.13051","title":"Hierarchical Semantic Contrast for Scene-aware Video Anomaly Detection","created":"2023-03-23","cited_by_count":39,"area":null},{"id":"2108.11244","title":"Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction","created":"2021-08-25","cited_by_count":37,"area":null},{"id":"2306.12041","title":"Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors","created":"2023-06-21","cited_by_count":37,"area":null},{"id":"2108.03825","title":"Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video","created":"2021-08-09","cited_by_count":32,"area":null},{"id":"2110.09742","title":"Learning Not to Reconstruct Anomalies","created":"2021-10-19","cited_by_count":31,"area":null},{"id":"2104.12961","title":"Unsupervised Multi-Source Domain Adaptation for Person Re-Identification","created":"2021-04-27","cited_by_count":30,"area":null},{"id":"2310.02835","title":"Delving into CLIP latent space for Video Anomaly Recognition","created":"2023-10-04","cited_by_count":27,"area":null},{"id":"2409.05383","title":"Deep Learning for Video Anomaly Detection: A Review","created":"2024-09-09","cited_by_count":27,"area":null},{"id":"2110.09768","title":"Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection","created":"2021-10-19","cited_by_count":26,"area":null},{"id":"2208.11113","title":"Towards Open Set Video Anomaly Detection","created":"2022-08-23","cited_by_count":26,"area":null},{"id":"2211.00882","title":"DyAnNet: A Scene Dynamicity Guided Self-Trained Video Anomaly Detection Network","created":"2022-11-02","cited_by_count":26,"area":null},{"id":"2203.12840","title":"Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection","created":"2022-03-24","cited_by_count":23,"area":null},{"id":"2308.11072","title":"TeD-SPAD: Temporal Distinctiveness for Self-supervised Privacy-preservation for video Anomaly Detection","created":"2023-08-21","cited_by_count":23,"area":null},{"id":"2210.09452","title":"Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning","created":"2022-10-17","cited_by_count":22,"area":null},{"id":"2302.04549","title":"Weakly Supervised Anomaly Detection: A Survey","created":"2023-02-09","cited_by_count":22,"area":null},{"id":"2306.08194","title":"Learning on Graphs under Label Noise","created":"2023-06-14","cited_by_count":22,"area":null},{"id":"2310.04987","title":"Data-centric Graph Learning: A Survey","created":"2023-10-08","cited_by_count":22,"area":null},{"id":"2311.15367","title":"BatchNorm-based Weakly Supervised Video Anomaly Detection","created":"2023-11-26","cited_by_count":22,"area":null},{"id":"2108.01975","title":"Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement","created":"2021-08-04","cited_by_count":21,"area":null},{"id":"2203.12121","title":"Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection","created":"2022-03-23","cited_by_count":20,"area":null},{"id":"2206.04149","title":"A Survey of Graph-based Deep Learning for Anomaly Detection in Distributed Systems","created":"2022-06-08","cited_by_count":20,"area":null},{"id":"2302.00058","title":"Graph Anomaly Detection in Time Series: A Survey","created":"2023-01-31","cited_by_count":18,"area":null},{"id":"2405.19387","title":"Video Anomaly Detection in 10 Years: A Survey and Outlook","created":"2024-05-29","cited_by_count":18,"area":null},{"id":"2510.22693","title":"VADTree: Explainable Training-Free Video Anomaly Detection via Hierarchical Granularity-Aware Tree","created":"2025-10-26","cited_by_count":18,"area":null},{"id":"2103.14242","title":"Learning from Pixel-Level Label Noise: A New Perspective for Semi-Supervised Semantic Segmentation","created":"2021-03-26","cited_by_count":16,"area":null},{"id":"2106.08613","title":"FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation","created":"2021-06-16","cited_by_count":15,"area":null},{"id":"2212.05532","title":"Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges","created":"2022-12-11","cited_by_count":15,"area":null},{"id":"2309.16309","title":"Weakly-Supervised Video Anomaly Detection with Snippet Anomalous Attention","created":"2023-09-28","cited_by_count":15,"area":null},{"id":"2203.13716","title":"Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies","created":"2022-03-25","cited_by_count":14,"area":null},{"id":"2406.18815","title":"MissionGNN: Hierarchical Multimodal GNN-based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation","created":"2024-06-27","cited_by_count":14,"area":null},{"id":"2104.14770","title":"Cleaning Label Noise with Clusters for Minimally Supervised Anomaly Detection","created":"2021-04-30","cited_by_count":13,"area":null},{"id":"2310.17650","title":"A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection","created":"2023-10-26","cited_by_count":13,"area":null},{"id":"2203.13704","title":"Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Videos","created":"2022-03-25","cited_by_count":12,"area":null},{"id":"2208.09779","title":"Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation","created":"2022-08-21","cited_by_count":12,"area":null},{"id":"2305.18797","title":"Learning Weakly Supervised Audio-Visual Violence Detection in Hyperbolic Space","created":"2023-05-30","cited_by_count":12,"area":null},{"id":"2411.14565","title":"Privacy-Preserving Video Anomaly Detection: A Survey","created":"2024-11-21","cited_by_count":11,"area":null},{"id":"2502.18863","title":"Sherlock: Towards Multi-scene Video Abnormal Event Extraction and Localization via a Global-local Spatial-sensitive LLM","created":"2025-02-26","cited_by_count":11,"area":null},{"id":"2212.07144","title":"Uncertain Facial Expression Recognition via Multi-task Assisted Correction","created":"2022-12-14","cited_by_count":10,"area":null},{"id":"2303.18044","title":"Long-Short Temporal Co-Teaching for Weakly Supervised Video Anomaly Detection","created":"2023-03-31","cited_by_count":10,"area":null},{"id":"2503.03562","title":"Towards Visual Discrimination and Reasoning of Real-World Physical Dynamics: Physics-Grounded Anomaly Detection","created":"2025-03-05","cited_by_count":10,"area":null},{"id":"2403.13417","title":"Diversified and Personalized Multi-rater Medical Image Segmentation","created":"2024-03-20","cited_by_count":9,"area":null},{"id":"2204.11053","title":"Uncertain Label Correction via Auxiliary Action Unit Graphs for Facial Expression Recognition","created":"2022-04-23","cited_by_count":8,"area":null},{"id":"2208.05636","title":"Locality-aware Attention Network with Discriminative Dynamics Learning for Weakly Supervised Anomaly Detection","created":"2022-08-11","cited_by_count":8,"area":null},{"id":"2303.10704","title":"PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies","created":"2023-03-19","cited_by_count":8,"area":null},{"id":"2503.13160","title":"Language-guided Open-world Video Anomaly Detection under Weak Supervision","created":"2025-03-17","cited_by_count":8,"area":null},{"id":"2508.06350","title":"Aligning Effective Tokens with Video Anomaly in Large Language Models","created":"2025-08-08","cited_by_count":8,"area":null},{"id":"2108.08996","title":"Weakly-supervised Joint Anomaly Detection and Classification","created":"2021-08-20","cited_by_count":7,"area":null},{"id":"2202.06503","title":"Adaptive Graph Convolutional Networks for Weakly Supervised Anomaly Detection in Videos","created":"2022-02-14","cited_by_count":7,"area":null},{"id":"2209.12074","title":"Self-supervised Learning for Unintentional Action Prediction","created":"2022-09-24","cited_by_count":7,"area":null},{"id":"2403.06154","title":"GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection","created":"2024-03-10","cited_by_count":7,"area":null},{"id":"2411.10945","title":"Anomaly Detection for People with Visual Impairments Using an Egocentric 360-Degree Camera","created":"2024-11-17","cited_by_count":7,"area":null},{"id":"2504.04495","title":"AVadCLIP: Audio-Visual Collaboration for Robust Video Anomaly Detection","created":"2025-04-06","cited_by_count":7,"area":null},{"id":"2203.08942","title":"ABN: Agent-Aware Boundary Networks for Temporal Action Proposal Generation","created":"2022-03-16","cited_by_count":6,"area":null},{"id":"2210.06688","title":"Overlooked Video Classification in Weakly Supervised Video Anomaly Detection","created":"2022-10-13","cited_by_count":6,"area":null},{"id":"2408.05191","title":"Cross-Domain Learning for Video Anomaly Detection with Limited Supervision","created":"2024-08-09","cited_by_count":6,"area":null},{"id":"2209.11477","title":"Weakly Supervised Two-Stage Training Scheme for Deep Video Fight Detection Model","created":"2022-09-23","cited_by_count":5,"area":null},{"id":"2401.13551","title":"Interleaving One-Class and Weakly-Supervised Models with Adaptive Thresholding for Unsupervised Video Anomaly Detection","created":"2024-01-24","cited_by_count":5,"area":null},{"id":"2103.10502","title":"Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies","created":"2021-03-18","cited_by_count":4,"area":null},{"id":"2106.05003","title":"Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing","created":"2021-06-09","cited_by_count":4,"area":null},{"id":"2206.01524","title":"Anomaly detection in surveillance videos using transformer based attention model","created":"2022-06-03","cited_by_count":4,"area":null},{"id":"2212.10207","title":"Graph Neural Networks in Computer Vision -- Architectures, Datasets and Common Approaches","created":"2022-12-20","cited_by_count":4,"area":null},{"id":"2301.07923","title":"Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detection","created":"2023-01-19","cited_by_count":4,"area":null},{"id":"2405.04405","title":"Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation","created":"2024-05-07","cited_by_count":4,"area":null},{"id":"2412.00348","title":"Vision Technologies with Applications in Traffic Surveillance Systems: A Holistic Survey","created":"2024-11-30","cited_by_count":4,"area":null},{"id":"2506.23282","title":"Autoregressive Denoising Score Matching is a Good Video Anomaly Detector","created":"2025-06-29","cited_by_count":4,"area":null},{"id":"2507.21649","title":"The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM","created":"2025-07-29","cited_by_count":4,"area":null},{"id":"2112.06320","title":"Anomaly Crossing: New Horizons for Video Anomaly Detection as Cross-domain Few-shot Learning","created":"2021-12-12","cited_by_count":3,"area":null},{"id":"2207.11838","title":"SAVCHOI: Detecting Suspicious Activities using Dense Video Captioning with Human Object Interactions","created":"2022-07-24","cited_by_count":3,"area":null},{"id":"2211.13471","title":"Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition","created":"2022-11-24","cited_by_count":3,"area":null},{"id":"2211.17071","title":"Interpreting Vulnerabilities of Multi-Instance Learning to Adversarial Perturbations","created":"2022-11-30","cited_by_count":3,"area":null},{"id":"2304.11905","title":"Data-driven Knowledge Fusion for Deep Multi-instance Learning","created":"2023-04-24","cited_by_count":3,"area":null},{"id":"2404.15033","title":"IPAD: Industrial Process Anomaly Detection Dataset","created":"2024-04-23","cited_by_count":3,"area":null},{"id":"2406.02831","title":"Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection","created":"2024-06-05","cited_by_count":3,"area":null},{"id":"2505.13123","title":"Just Dance with $\\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection","created":"2025-05-19","cited_by_count":3,"area":null},{"id":"2505.19022","title":"Rethinking Metrics and Benchmarks of Video Anomaly Detection","created":"2025-05-25","cited_by_count":3,"area":null},{"id":"2506.13095","title":"Learning Event Completeness for Weakly Supervised Video Anomaly Detection","created":"2025-06-16","cited_by_count":3,"area":null},{"id":"2603.00550","title":"Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning","created":"2026-02-28","cited_by_count":3,"area":null},{"id":"2104.06813","title":"Global Information Guided Video Anomaly Detection","created":"2021-04-14","cited_by_count":2,"area":null},{"id":"2105.04302","title":"Video Anomaly Detection By The Duality Of Normality-Granted Optical Flow","created":"2021-05-10","cited_by_count":2,"area":null},{"id":"2112.05410","title":"Multimedia Datasets for Anomaly Detection: A Review","created":"2021-12-10","cited_by_count":2,"area":null},{"id":"2203.13610","title":"Learning to Adapt to Unseen Abnormal Activities under Weak Supervision","created":"2022-03-25","cited_by_count":2,"area":null}],"next_cursor":"100"}