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4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview

Benjamin Kiefer, Jan Lukas Augustin, Jon Muhovič, Mingi Jeong, Arnold Wiliem, Janez Pers, Matej Kristan, Alberto Quattrini Li, Matija Teršek, Josip Šarić, Arpita Vats, Dominik Hildebrand, Rafia Rahim, Mahmut Karaaslan, Arpit Vaishya, Steve Xie, Ersin Kaya, Akib Mashrur, Tze-Hsiang Tang, Chun-Ming Tsai, Jun-Wei Hsieh, Ming-Ching Chang, Wonwoo Jo, Doyeon Lee, Yusi Cao, Lingling Li, Vinayak Nageli, Arshad Jamal, Gorthi Rama Krishna Sai Subrahmanyam, Jemo Maeng, Seongju Lee, Kyoobin Lee, Xu Liu, LiCheng Jiao, Jannik Sheikh, Martin Weinmann, Ivan Martinović, Jose Mateus Raitz Persch, Rahul Harsha Cheppally, Mehmet E. Belviranli, Dimitris Gahtidis, Hyewon Chun, Sangmun Lee, Philipp Gorczak, Hansol Kim, Jeeyeon Jeon, Borja Carrillo Perez, Jiahui Wang, Sangmin Park, Andreas Michel, Jannick Kuester, Bettina Felten, Wolfgang Gross, Yuan Feng, Justin Davis

arXiv:2604.13244Published April 14, 20260 citations
  • cs.CV
  • cs.AI
  • cs.RO

Abstract

The 4th Workshop on Maritime Computer Vision (MaCVi) is organized as part of CVPR 2026. This edition features five benchmark challenges with emphasis on both predictive accuracy and embedded real-time feasibility. This report summarizes the MaCVi 2026 challenge setup, evaluation protocols, datasets, and benchmark tracks, and presents quantitative results, qualitative comparisons, and cross-challenge analyses of emerging method trends. We also include technical reports from top-performing teams to highlight practical design choices and lessons learned across the benchmark suite. Datasets, leaderboards, and challenge resources are available at https://macvi.org/workshop/cvpr26.

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