As computer vision surges to the forefront of maritime and freshwater technology, its transformative potential is clear. It's ushering in unprecedented advancements, from critical search and rescue missions to dynamic aquatic life monitoring.
We're proud to announce the Maritime Computer Vision Initiative (MaCVi). MaCVi aims to gather leading experts, foster collaboration, and accelerate the integration of computer vision into all kinds of maritime domains.
On this page, you'll find useful information on benchmark datasets, scoreboards, past & upcoming workshops and more. Welcome to MaCVi.
If you this initiative useful, consider citing the following paper, from which it originated:
@article{kiefer20221st,
title={1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results},
author={Kiefer, Benjamin and Kristan, Matej and Per{\v{s}}, Janez and {\v{Z}}ust, Lojze and Poiesi, Fabio and Andrade, Fabio Augusto de Alcantara and Bernardino, Alexandre and Dawkins, Matthew and Raitoharju, Jenni and Quan, Yitong and others},
journal={arXiv preprint arXiv:2211.13508},
year={2022}
}
@inproceedings{varga2022seadronessee,
title={Seadronessee: A maritime benchmark for detecting humans in open water},
author={Varga, Leon Amadeus and Kiefer, Benjamin and Messmer, Martin and Zell, Andreas},
booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={2260--2270},
year={2022}
}
@article{bovcon2021mods,
title={MODS--A USV-oriented object detection and obstacle segmentation benchmark},
author={Bovcon, Borja and Muhovi{\v{c}}, Jon and Vranac, Du{\v{s}}ko and Mozeti{\v{c}}, Dean and Per{\v{s}}, Janez and Kristan, Matej},
journal={IEEE Transactions on Intelligent Transportation Systems},
year={2021},
publisher={IEEE}
}
@InProceedings{Zust2023LaRS,
title={LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark},
author={{\v{Z}}ust, Lojze and Per{\v{s}}, Janez and Kristan, Matej},
booktitle={International Conference on Computer Vision (ICCV)},
year={2023}
}