30 datasets found

The dataset used for local anomaly detection in videos using object-centric adversarial learning.

A video anomaly detection dataset for a crowded scene, containing 11 short clips of people meandering around an outdoor field, courtyard, or indoor foyer.

Video anomaly detection (VAD) aims to temporally locate abnormal events in a video. Existing works mostly rely on training deep models to learn the distribution of normality...

Towards interpretable video anomaly detection

Anomaly detection in video via self-supervised and multi-task learning

A future frame prediction for anomaly detection

A new dataset and evaluation protocol for video anomaly detection

Video Anomaly Detection as a probabilistic analysis of object bounding boxes

A large-scale colonoscopy video dataset containing diverse polyps.

A large-scale colonoscopy video dataset containing 61 normal videos and 102 abnormal videos for training, and 30 normal videos and 60 abnormal videos for testing.

Real-world anomaly detection in surveillance videos.

Video anomaly detection has great potential in enhancing safety in the production and monitoring of crucial areas. Currently, most video anomaly detection methods are based on...

Abnormal Event Detection at 150 FPS in MATLAB dataset

A new large-scale dataset for video anomaly detection, Street Scene, contains 46 training video sequences and 35 testing video sequences taken from a static USB camera looking...

UCSD Ped1 & Ped2 dataset for single-scene video anomaly detection

Anomalies are rare and anomaly detection is often therefore framed as One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC techniques constrain the...

The UCF-Crime and XD-Violence datasets are used for weakly supervised video anomaly detection.

Object-centric auto-encoders and dummy anomalies for abnormal event detection in video.

Clustering driven deep autoencoder for video anomaly detection.

Video anomaly detection is often seen as one-class classification (OCC) problem due to the limited availability of anomaly examples.