Data to 7 Oct 2026

Abnormal Event Detection in Videos using Spatiotemporal Autoencoder

arXiv 1701.01546 ↗First posted 6 Jan 2017cs.CVcited by 57

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Abstract (arXiv)

We present an efficient method for detecting anomalies in videos. Recent applications of convolutional neural networks have shown promises of convolutional layers for object detection and recognition, especially in images. However, convolutional neural networks are supervised and require labels as learning signals. We propose a spatiotemporal architecture for anomaly detection in videos including crowded scenes. Our architecture includes two main components, one for spatial feature representation, and one for learning the temporal evolution of the spatial features. Experimental results on Avenue, Subway and UCSD benchmarks confirm that the detection accuracy of our method is comparable to state-of-the-art methods at a considerable speed of up to 140 fps.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jan 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 19; 2022: 15; 2023: 7; 2024: 9; 2025: 5; 2026: 2.

57 papers.

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2021Learning Normal Dynamics in Videos with Meta Prototype Networkcited by 71
2023Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Modelscited by 59
2022Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detectioncited by 47
2023Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detectioncited by 42
2021Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detectioncited by 31
2021A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videoscited by 28
2024Networking Systems for Video Anomaly Detection: A Tutorial and Surveycited by 21
2024Video Anomaly Detection in 10 Years: A Survey and Outlookcited by 18
2021DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behaviorcited by 17
2024TrafficVLM: A Controllable Visual Language Model for Traffic Video Captioningcited by 17
2021FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformationcited by 15
2021OLED: One-Class Learned Encoder-Decoder Network with Adversarial Context Masking for Novelty Detectioncited by 14

38 more

2022Deep Learning Serves Traffic Safety Analysis: A Forward-looking Reviewcited by 13
2022Anomaly Detection in Aerial Videos with Transformerscited by 11
2024Text-Driven Traffic Anomaly Detection with Temporal High-Frequency Modeling in Driving Videoscited by 9
2021A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methodscited by 7
2022BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detectioncited by 7
2021A Modular and Unified Framework for Detecting and Localizing Video Anomaliescited by 6
2022Multi-Task Learning based Video Anomaly Detection with Attentioncited by 6
2021Noise Reduction in X-ray Photon Correlation Spectroscopy with Convolutional Neural Networks Encoder-Decoder Modelscited by 5
2022Weakly Supervised Two-Stage Training Scheme for Deep Video Fight Detection Modelcited by 5
2021Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomaliescited by 4
2022An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving Videoscited by 4
2023Memory-augmented Online Video Anomaly Detectioncited by 4
2025CBIL: Collective Behavior Imitation Learning for Fish from Real Videoscited by 4
2021Feature Selection for Multivariate Time Series via Network Pruningcited by 3
2022Visual anomaly detection in video by variational autoencodercited by 3
2022Object Class Aware Video Anomaly Detection through Image Translationcited by 3
2025When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Networkcited by 3
2021Video Anomaly Detection By The Duality Of Normality-Granted Optical Flowcited by 2
2023A Memory-Augmented Multi-Task Collaborative Framework for Unsupervised Traffic Accident Detection in Driving Videoscited by 2
2025VADER: Towards Causal Video Anomaly Understanding with Relation-Aware Large Language Modelscited by 2
2022Contextual Information Based Anomaly Detection for a Multi-Scene UAV Aerial Videoscited by 1
2022Towards Realistic Out-of-Distribution Detection: A Novel Evaluation Framework for Improving Generalization in OOD Detectioncited by 1
2023Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encodercited by 1
2024What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised Horizoncited by 1
2025An Expert Ensemble for Detecting Anomalous Scenes, Interactions, and Behaviors in Autonomous Drivingcited by 1
2025Pathology-Informed Latent Diffusion Model for Anomaly Detection in Lymph Node Metastasiscited by 1
2021Anomaly Recognition from surveillance videos using 3D Convolutional Neural Networkscited by 0
2021"Forget" the Forget Gate: Estimating Anomalies in Videos using Self-contained Long Short-Term Memory Networkscited by 0
2021Generalized One-Class Learning Using Pairs of Complementary Classifierscited by 0
2021Anomaly Detection Based on Multiple-Hypothesis Autoencodercited by 0
2021Normal Learning in Videos with Attention Prototype Networkcited by 0
20213D-MOV: Audio-Visual LSTM Autoencoder for 3D Reconstruction of Multiple Objects from Videocited by 0
2021Automated Antenna Testing Using Encoder-Decoder-based Anomaly Detectioncited by 0
2022Anomaly detection using prediction error with Spatio-Temporal Convolutional LSTMcited by 0
2022Anomaly Detection with Adversarially Learned Perturbations of Latent Spacecited by 0
2022Augment to Detect Anomalies with Continuous Labellingcited by 0
2022Leveraging Trajectory Prediction for Pedestrian Video Anomaly Detectioncited by 0
2023Interruptions detection in video conferencescited by 0

50 most cited of 57 All 57 (JSON)