1st Workshop on Maritime Computer Vision (MaCVi) 2023 : Challenge Results
Kiefer, B., Kristan, M., Pers, J., Zust, L., Poiesi, F., De Alcantara Andrade, F. A., Bernardino, A., Dawkins, M., Raitoharju, J., Quan, Y., Atmaca, A., Hofer, T., Zhang, Q., Xu, Y., Zhang, J., Tao, D., Sommer, L., Spraul, R., Zhao, H., . . . Yang, M.-T. (2023). 1st Workshop on Maritime Computer Vision (MaCVi) 2023 : Challenge Results. In WACVW 2023 : IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (pp. 265-302). IEEE. Proceedings (IEEE Winter Conference on Applications of Computer Vision Workshops). https://doi.org/10.1109/wacvw58289.2023.00033
Julkaistu sarjassa
Proceedings (IEEE Winter Conference on Applications of Computer Vision Workshops)Tekijät
Päivämäärä
2023Tekijänoikeudet
© 2023 IEEE
The 1 st Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Mar-itime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new benchmark, called SeaDronesSee Object Detection v2, which extends the previous benchmark by including more classes and footage. We provide statistical and qualitative analyses, and assess trends in the best-performing method-ologies of over 130 submissions. The methods are sum-marized in the appendix. The datasets, evaluation code and the leaderboard are publicly available (https://seadronessee.cs.uni-tuebingen.de/macvi).
Julkaisija
IEEEEmojulkaisun ISBN
979-8-3503-2057-2Konferenssi
IEEE Winter Applications and Computer Vision WorkshopsKuuluu julkaisuun
WACVW 2023 : IEEE/CVF Winter Conference on Applications of Computer Vision WorkshopsISSN Hae Julkaisufoorumista
2572-4398Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/176862364
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Lisätietoja rahoituksesta
This work was supported by the SHIELD project under the European Union’s Joint Programming Initiative – Cultural Heritage, Conservation, Protection and Use joint call, Slovenian Research Agency (ARRS) project J2-2506 and programs P2-0214 and P2-0095, the German Ministry for Economic Affairs and Energy, Project Avalon, FKZ: 3SX481B and Sentient Vision Systems for sponsoring prizes for the UAV-based Object Detection v2 challenge. ...Lisenssi
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