NWPU Campus dataset
Congqi
Cao
Yue Lu
Peng
Wang
Yanning Zhang
National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology (ASGO), School of Computer Science, Northwestern Polytechnical University, China
Paper: A New Comprehensive Benchmark for Semi-supervised Video Anomaly Detection and Anticipation
NWPU Campus is a dataset proposed for (semi-supervised) video anomaly detection (VAD) and video anomaly
anticipation (VAA).
It is currently the largest and most complex dataset in its field with 43 scenes, 28 classes of anomalous
events and 16 hours of videos.
Especially, it contains scene-dependent anomalies, which means an event may be normal in one scene but
abnormal in another.
Introduction
A number of normal and anomalous events in different scenes are displayed in Figure 1. All the 28 classes of
anomalous events are listed in Table 1.
Table 2 and Figure 2 show the statistics of the dataset, including durations and distributions.
Samples
Figure 1. Samples from the proposed NWPU Campus dataset. The samples in the first column are normal
events,
while the others are different types of anomalous events.
Classes of anomalies
Table 1. The list of anomaly classes in NWPU Campus dataset. "s.d." stands for a scene-dependent
anomaly.
| Climbing fence |
Car crossing square |
Cycling on footpath (s.d.) |
Kicking trash can |
| Jaywalking |
Snatching bag |
Crossing lawn |
Wrong turn (s.d.) |
| Cycling on square |
Chasing |
Loitering |
Scuffle |
| Littering |
Forgetting backpack |
U-turn |
Battering |
| Driving on wrong side |
Falling |
Suddenly stopping cycling in the middle of the road |
Group conflict |
| Climbing tree |
Stealing |
Illegal parking |
Trucks (s.d.) |
| Protest |
Playing with water |
Photographing in restricted area (s.d.) |
Dogs |
Statistics
Table 2. Frame count and duration of the NWPU Campus dataset.
| NWPU Campus (25 FPS) |
| 1,466,073 (16.29h) |
| Training frames |
Testing frames |
| 1,082,014 (12.02h) |
384,059 (4.27h) |
| Normal |
Normal |
Abnormal |
| 1,082,014 (12.02h) |
318,793 (3.54h) |
65,266 (0.73h) |
Figure 2. The distributions of training and testing videos according to duration (a),
and abnormal
testing videos according to the percentage of abnormal frames in each video (b).
Download the dataset
Terms & Conditions of use
The NWPU Campus dataset is released for academic research only, and is free to researchers from educational
or
research institutes for non-commercial purposes.
The use of the NWPU Campus dataset is governed by the following terms and conditions:
-
Without the expressed permission of the ASGO Lab, any of the following will be considered illegal:
redistribution, derivation or generation of a new dataset from this dataset, and commercial usage of any
of these datasets in any way or form, either partially or in its entirety.
-
For the sake of privacy, images of all subjects in any of these datasets are only allowed for the
demonstration in academic publications and presentations.
-
All users of NWPU Campus dataset agree to indemnify, defend and hold harmless,
the ASGO Lab and its officers, employees, and agents, individually and collectively, from any and all
losses, expenses, and damages.
We hold no liability for any undesirable consequences of using the dataset. All rights of the NWPU Campus dataset are reserved.
Download
There are 305 training videos and 242 testing videos in the NWPU Campus dataset. All of the videos amount to 76.6 GB in disk space.
Please note that most of the abnormal behaviors in the dataset are performed with careful protection.
Do not mimic these behaviors in reality.
Download from BaiduYun (code: il54) [101 downloads] or Google Drive
Citation
@InProceedings{Cao_2023_CVPR,
author = {Cao, Congqi and Lu, Yue and Wang, Peng and Zhang, Yanning},
title = {A New Comprehensive Benchmark for Semi-Supervised Video Anomaly Detection and Anticipation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
pages = {20392-20401}
}
Paper link