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

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

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

Useful Toolbox for Anomaly Detection

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

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

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

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

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

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

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

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