mlsanityData to 14 Oct 2026

Learning Deep Representations of Appearance and Motion for Anomalous Event Detection

arXiv 1510.01553 ↗First posted 6 Oct 2015cs.CVcited by 75

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Abstract (arXiv)

We present a novel unsupervised deep learning framework for anomalous event detection in complex video scenes. While most existing works merely use hand-crafted appearance and motion features, we propose Appearance and Motion DeepNet (AMDN) which utilizes deep neural networks to automatically learn feature representations. To exploit the complementary information of both appearance and motion patterns, we introduce a novel double fusion framework, combining both the benefits of traditional early fusion and late fusion strategies. Specifically, stacked denoising autoencoders are proposed to separately learn both appearance and motion features as well as a joint representation (early fusion). Based on the learned representations, multiple one-class SVM models are used to predict the anomaly scores of each input, which are then integrated with a late fusion strategy for final anomaly detection. We evaluate the proposed method on two publicly available video surveillance datasets, showing competitive performance with respect to state of the art approaches.

Key facts. Cited by 75 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Oct 2015.

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Citing papers per year: 2021: 25; 2022: 21; 2023: 8; 2024: 10; 2025: 8; 2026: 3.

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  1. 2021Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learningcited by 230
  2. 2022Generative Cooperative Learning for Unsupervised Video Anomaly Detectioncited by 102
  3. 2021Deep One-Class Classification via Interpolated Gaussian Descriptorcited by 67
  4. 2023Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detectioncited by 64
  5. 2023Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Modelscited by 59
  6. 2024Text Prompt with Normality Guidance for Weakly Supervised Video Anomaly Detectioncited by 49
  7. 2024Hawk: Learning to Understand Open-World Video Anomaliescited by 49
  8. 2022Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detectioncited by 47
  9. 2022SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detectioncited by 45
  10. 2021Offline Reinforcement Learning as Anti-Explorationcited by 44
  11. 2021Cross-modal Consensus Network for Weakly Supervised Temporal Action Localizationcited by 34
  12. 2021Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Videocited by 32
38 more
  1. 2021Learning Not to Reconstruct Anomaliescited by 31
  2. 2022Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detectioncited by 27
  3. 2024Deep Learning for Video Anomaly Detection: A Reviewcited by 27
  4. 2022EVAL: Explainable Video Anomaly Localizationcited by 19
  5. 2022Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detectioncited by 18
  6. 2021Learnable Locality-Sensitive Hashing for Video Anomaly Detectioncited by 17
  7. 2021Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Reviewcited by 15
  8. 2024Gazing Into Missteps: Leveraging Eye-Gaze for Unsupervised Mistake Detection in Egocentric Videos of Skilled Human Activitiescited by 15
  9. 2021Behavior-Driven Synthesis of Human Dynamicscited by 14
  10. 2021OLED: One-Class Learned Encoder-Decoder Network with Adversarial Context Masking for Novelty Detectioncited by 14
  11. 2022Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomaliescited by 14
  12. 2022Deep Learning Serves Traffic Safety Analysis: A Forward-looking Reviewcited by 13
  13. 2022Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Videoscited by 12
  14. 2021Context-Dependent Anomaly Detection for Low Altitude Traffic Surveillancecited by 10
  15. 2021Anomaly Detection in Video Sequences: A Benchmark and Computational Modelcited by 10
  16. 2023Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approachcited by 10
  17. 2022Adversarial Machine Learning Attacks Against Video Anomaly Detection Systemscited by 9
  18. 2021Communication-Efficient Split Learning Based on Analog Communication and Over the Air Aggregationcited by 8
  19. 2021A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methodscited by 7
  20. 2021A Modular and Unified Framework for Detecting and Localizing Video Anomaliescited by 6
  21. 2024Cross-Domain Learning for Video Anomaly Detection with Limited Supervisioncited by 6
  22. 2022Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Modelscited by 5
  23. 2022Anomaly detection in surveillance videos using transformer based attention modelcited by 4
  24. 2025The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLMcited by 4
  25. 2021CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rayscited by 3
  26. 2021PANDA : Perceptually Aware Neural Detection of Anomaliescited by 3
  27. 2023Multi-module based CVAE to predict HVCM faults in the SNS acceleratorcited by 3
  28. 2024Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detectioncited by 3
  29. 2021Video Anomaly Detection By The Duality Of Normality-Granted Optical Flowcited by 2
  30. 2022Learning to Adapt to Unseen Abnormal Activities under Weak Supervisioncited by 2
  31. 2025Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigationcited by 2
  32. 2021Anomaly Detection with Prototype-Guided Discriminative Latent Embeddingscited by 1
  33. 2021Video Abnormal Event Detection by Learning to Complete Visual Cloze Testscited by 1
  34. 2022Contextual Information Based Anomaly Detection for a Multi-Scene UAV Aerial Videoscited by 1
  35. 2022Look at Adjacent Frames: Video Anomaly Detection without Offline Trainingcited by 1
  36. 2022Spatio-Temporal Relation Learning for Video Anomaly Detectioncited by 1
  37. 2022Towards Realistic Out-of-Distribution Detection: A Novel Evaluation Framework for Improving Generalization in OOD Detectioncited by 1
  38. 2023CNTS: Cooperative Network for Time Seriescited by 1

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