Kiefer, BenjaminKristan, MatejPers, JanezZust, LojzePoiesi, FabioAndrade, Fabio Augusto de AlcantaraBernardino, AlexandreDawkins, MatthewRaitoharju, JenniQuan, YitongAtmaca, AdemHoefer, TimonZhang, QimingXu, YufeiZhang, JingTao, DachengSommer, LarsSpraul, RaphaelZhao, HangyueZhang, HongpuZhao, YanyunAugustin, Jan LukasJeon, Eui-IkLee, ImpyeongZedda, LucaLoddo, AndreaDi Ruberto, CeciliaVerma, SagarGupta, SiddharthMuralidhara, ShishirHegde, NiharikaXing, DaitaoEvangeliou, NikolaosTzes, AnthonyBartl, VojtechSpanhel, JakubHerout, AdamBhowmik, NeelanjanBreckon, Toby P.Kundargi, ShivanandAnvekar, TejasTabib, Ramesh AshokMudengudi, UmaVats, ArpitaSong, YangLiu, DelongLi, YonglinLi, ShumanTan, ChenhaoLan, LongSomers, VladimirDe Vleeschouwer, ChristopheAlahi, AlexandreHuang, Hsiang-WeiYang, Cheng-YenHwang, Jenq-NengKim, Pyong-KunKim, KwangjuLee, KyoungohJiang, ShuaiLi, HaiwenZheng, ZiqiangVu, Tuan-AnhNguyen-Truong, HaiYeung, Sai-KitJia, ZhuangYang, SophiaHsu, Chih-ChungHou, Xiu-YuJhang, Yu-AnYang, SimonYang, Mau-Tsuen2023-06-052023-06-052023-06-052023-01-0110.1109/WACVW58289.2023.00033https://infoscience.epfl.ch/handle/20.500.14299/198120WOS:000971997900029The 1st 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 Maritime 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 methodologies of over 130 submissions. The methods are summarized in the appendix. The datasets, evaluation code and the leaderboard are publicly available (https:// seadronessee.cs.uni-tuebingen.de/macvi).Computer Science, Artificial IntelligenceImaging Science & Photographic TechnologyComputer ScienceImaging Science & Photographic Technologytext::conference output::conference proceedings::conference paper