Papers for Video Anomaly Detection, released codes collection, Performance Comparision.

ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

🔥[NeurIPS 2024] Official Implementation of Hawk: Learning to Understand Open-World Video Anomalies

A curated collection of papers, code, datasets, and utilities for Video Anomaly Detection, updated every Friday.

Official codes for CVPR2021 paper "MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection"

[CVPR 2025 Highlight] Official implementation of "Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity"

This is an official implementation for "Attention-based Residual Autoencoder for Video Anomaly Detection".

Useful Toolbox for Anomaly Detection

An Attribute-based Method for Video Anomaly Detection (TMLR 2025)

Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events. Oral paper in ACM Multimedia 2020.

Official code for AAAI2023 paper "Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection"

This is the code repo for the paper VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models (CVPR 2025).

Frame level anomaly detection and localization in videos using auto-encoders

Anomaly Detection in Video via Self-Supervised and Multi-Task Learning

Pytorch Re-implement of ano_pre_cvpr2018, flownet2 / lite-flownet used.

This is an official implement for "HSTforU: Anomaly Detection in Aerial and Ground-based Videos with Hierarchical Spatio-Temporal Transformer for U-net"

A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video

[ICME 2025 Oral] Official implementation of "GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection"

[ICIP 2023] Exploring Diffusion Models For Unsupervised Video Anomaly Detection

[IEEE TII 2025] Official Implementation for "Dual-Detector Reoptimization for Federated Weakly Supervised Video Anomaly Detection via Adaptive Dynamic Recursive Mapping"

[NAACL'25] Contains code and documentation for our VANE-Bench paper.

[NeurIPS 24] Implementation of "Advancing Video Anomaly Detection: A Concise Review and a New Dataset".

This is the official implementation of the paper namely Real-Time Anomaly Detection and Feature Analysis Based on Time Series for Surveillance Video.

Pytorch code for ECCVW 2022 paper "Consistency-based Self-supervised Learning for Temporal Anomaly Localization"

AutoregressModel-AE_VAD_CVPR2019 (code reimplemetation)

面向监控视频的异常行为检测系统设计。

Deep Anomaly Discovery from Unlabeled Videos via Normality Advantage and Self-Paced Refinement (CVPR2022)

A Self-Supervised Deep Learning Framework for Spatiotemporal Anomaly Detection in UAV Surveillance Videos

[Research] Self-Supervised Learning for Video Anomaly Detection: Jigsaw-VAD Approach