Official PyTorch Implementation of VADOR: Real World Video Anomaly Detection with Object Relations and Action
VADOR detects and localizes anomalies in time domain with leveraging action and relationships of objects in video
data/
├── Annotations
│ ├── Train
│ ├── Test
├── extracted_features
│ ├── test
│ ├── train
└ └── train_flip
If you find our work to be useful for your research, please consider citing.
@inproceedings{ozturk2021adnet,
title={ADNet: Temporal anomaly detection in surveillance videos},
author={{\"O}zt{\"u}rk, Halil {\.I}brahim and Can, Ahmet Burak},
booktitle={Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10--15, 2021, Proceedings, Part IV},
pages={88--101},
year={2021},
organization={Springer}
}