mlsanityData to 14 Oct 2026

Street Scene: A new dataset and evaluation protocol for video anomaly detection

arXiv 1902.05872 ↗First posted 15 Feb 2019cs.CVcited by 90

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Abstract (arXiv)

Progress in video anomaly detection research is currently slowed by small datasets that lack a wide variety of activities as well as flawed evaluation criteria. This paper aims to help move this research effort forward by introducing a large and varied new dataset called Street Scene, as well as two new evaluation criteria that provide a better estimate of how an algorithm will perform in practice. In addition to the new dataset and evaluation criteria, we present two variations of a novel baseline video anomaly detection algorithm and show they are much more accurate on Street Scene than two state-of-the-art algorithms from the literature.

Key facts. Cited by 90 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Feb 2019.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 15; 2022: 15; 2023: 11; 2024: 18; 2025: 19; 2026: 12.

90 papers.

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  1. 2021Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detectioncited by 119
  2. 2021UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detectioncited by 93
  3. 2022Normalizing Flows for Human Pose Anomaly Detectioncited by 60
  4. 2023Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Modelscited by 59
  5. 2024Advancing Video Anomaly Detection: A Concise Review and a New Datasetcited by 49
  6. 2022SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detectioncited by 45
  7. 2023A New Comprehensive Benchmark for Semi-supervised Video Anomaly Detection and Anticipationcited by 42
  8. 2023Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectorscited by 37
  9. 2022Self-Supervised Masked Convolutional Transformer Block for Anomaly Detectioncited by 34
  10. 2021Learning Not to Reconstruct Anomaliescited by 31
  11. 2024Deep Learning for Video Anomaly Detection: A Reviewcited by 27
  12. 2021Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detectioncited by 26
38 more
  1. 2022DyAnNet: A Scene Dynamicity Guided Self-Trained Video Anomaly Detection Networkcited by 26
  2. 2025VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-Tuningcited by 24
  3. 2024MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detectioncited by 22
  4. 2024Networking Systems for Video Anomaly Detection: A Tutorial and Surveycited by 21
  5. 2022Cross-Domain Video Anomaly Detection without Target Domain Adaptationcited by 20
  6. 2022EVAL: Explainable Video Anomaly Localizationcited by 19
  7. 2025UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networkscited by 19
  8. 2022Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detectioncited by 18
  9. 2022CHAD: Charlotte Anomaly Datasetcited by 18
  10. 2024Video Anomaly Detection in 10 Years: A Survey and Outlookcited by 18
  11. 2021Learnable Locality-Sensitive Hashing for Video Anomaly Detectioncited by 17
  12. 2021FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformationcited by 15
  13. 2024Do Language Models Understand Time?cited by 14
  14. 2024Context-aware Video Anomaly Detection in Long-Term Datasetscited by 11
  15. 2024Privacy-Preserving Video Anomaly Detection: A Surveycited by 11
  16. 2024Beyond Walking: A Large-Scale Image-Text Benchmark for Text-based Person Anomaly Searchcited by 11
  17. 2021Image/Video Deep Anomaly Detection: A Surveycited by 10
  18. 2023Survey on video anomaly detection in dynamic scenes with moving camerascited by 10
  19. 2023Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approachcited by 10
  20. 2022Adversarial Machine Learning Attacks Against Video Anomaly Detection Systemscited by 9
  21. 2024Exploring What Why and How: A Multifaceted Benchmark for Causation Understanding of Video Anomalycited by 9
  22. 2023PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomaliescited by 8
  23. 2025ComplexVAD: Detecting Interaction Anomalies in Videocited by 8
  24. 2025Track Any Anomalous Object: A Granular Video Anomaly Detection Pipelinecited by 8
  25. 2021Using Visual Anomaly Detection for Task Execution Monitoringcited by 7
  26. 2021Weakly-supervised Joint Anomaly Detection and Classificationcited by 7
  27. 2021A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methodscited by 7
  28. 2023Unveiling the Unseen: A Comprehensive Survey on Explainable Anomaly Detection in Images and Videoscited by 7
  29. 2025Sequential keypoint density estimator: an overlooked baseline of skeleton-based video anomaly detectioncited by 7
  30. 2021A Modular and Unified Framework for Detecting and Localizing Video Anomaliescited by 6
  31. 2024Towards Adaptive Human-centric Video Anomaly Detection: A Comprehensive Framework and A New Benchmarkcited by 6
  32. 2025SlowFastVAD: Video Anomaly Detection via Integrating Simple Detector and RAG-Enhanced Vision-Language Modelcited by 6
  33. 2021HR-Crime: Human-Related Anomaly Detection in Surveillance Videoscited by 5
  34. 2025A2Seek: Towards Reasoning-Centric Benchmark for Aerial Anomaly Understandingcited by 5
  35. 2025Pistachio: Towards Synthetic, Balanced, and Long-Form Video Anomaly Benchmarkscited by 5
  36. 2021Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomaliescited by 4
  37. 2022Concept Drift Challenge in Multimedia Anomaly Detection: A Case Study with Facial Datasetscited by 4
  38. 2023Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detectioncited by 4

50 most cited of 90 All 90 (JSON)