{"paper":{"title":"The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Aiguo Zheng, Alexander Klein, Andrea Loddo, Andreas Michel, Angel Bueno Rodriguez, Antje Alex, Arnold Wiliem, Benjamin Kiefer, Borja Carrillo-Perez, Cecilia Di Ruberto, Cheng-Yen Yang, Daniel Stadler, Edgardo Solano-Carrillo, Felix Sattler, Feng Chen, Hai Nguyen-Truong, Heng-Cheng Kuo, Hsiang-Wei Huang, Janez Per\\v{s}, Jenq-Neng Hwang, Jian Li, Jie Mei, Jun Xie, Kaer Huang, Kanokphan Lertniphonphan, Lars Sommer, Lixin Tian, Lojze \\v{Z}ust, Luca Zedda, Magdalena \\v{S}umunec, Martin Messmer, Martin Weinmann, Matej Fabijani\\'c, Matej Kristan, Matija Ter\\v{s}ek, Nadir Kapetanovi\\'c, Nguyen Thanh Thien, Quan-Dung Pham, Sai-Kit Yeung, Sheng-Yao Kuan, Tan-Sang Ha, Tuan-Anh Vu, Weitu Chong, Wolfgang Gross, Yannik Steiniger, Yuan Feng, Yuan-Hao Ho, Zhepeng Wang, Zhongyu Jiang","submitted_at":"2023-11-23T21:01:14Z","abstract_excerpt":"The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive ove"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.14762","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.14762/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}