/UMAD

[IROS 2024] UMAD: University of Macau Anomaly Detection Benchmark Dataset

Primary LanguageC++MIT LicenseMIT

UMAD: University of Macau Anomaly Detection Benchmark Dataset

IROS, 2024.
Dong Li, Lineng Chen, Cheng-Zhong Xu, Hui Kong

University of Macau
Corresponding Authors

Project Page Code&Datasets Paper Video

UMAD: University of Macau Anomaly Detection Benchmark Dataset

😊News

This work is maintaining. You can hit the STAR and WATCH to follow the updates.

  • 2024-8-22: UMAD paper sharing on arXiv~

  • 2024/6/30: UMAD has been accepted by IROS 2024! Thanks to everyone who participated in this project!

  • 2024/3/21: We have publicly released a supplementary video for the paper submission.

📝ToDo List

  • Make the project paper publicly available.
  • Open-source the UMAD dataset.
  • Open-source the UMAD-homo-eval dataset.
  • Open-source the code related to the datasets.

🔠Dataset

Dataset Structure

Anomaly Detection Benchmark

Change Detection Benchmark

💖Acknowledgement

The authors would like to thank the following people for their contributions to data collection and data annotation for this project: @Xiangyu QIN, @Shenbo WANG, @Kaijie YIN, @Shuhao ZHAI, @Xiaonan LI, @Beibei ZHOU, and @Hongzhi CHENG.

📰License

Our datasets and code is released under the MIT License (see LICENSE file for details).

⛅️Citing

If you find our work useful, please consider citing:

@article{li2024umad
  author    = {Li, Dong and Chen, Lineng and Xu, Cheng-Zhong and Kong, Hui},
  title     = {UMAD: University of Macau Anomaly Detection Benchmark Dataset},
  journal   = {arXiv preprint arXiv:2408.12527},
  year      = {2024},
}