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dc.contributor.authorKiefer, Benjamin
dc.contributor.authorKristan, Matej
dc.contributor.authorPers, Janez
dc.contributor.authorZust, Lojze
dc.contributor.authorPoiesi, Fabio
dc.contributor.authorDe Alcantara Andrade, Fabio Augusto
dc.contributor.authorBernardino, Alexandre
dc.contributor.authorDawkins, Matthew
dc.contributor.authorRaitoharju, Jenni
dc.contributor.authorQuan, Yitong
dc.contributor.authorAtmaca, Adem
dc.contributor.authorHofer, Timon
dc.contributor.authorZhang, Qiming
dc.contributor.authorXu, Yufei
dc.contributor.authorZhang, Jing
dc.contributor.authorTao, Dacheng
dc.contributor.authorSommer, Lars
dc.contributor.authorSpraul, Raphael
dc.contributor.authorZhao, Hangyue
dc.contributor.authorZhang, Hongpu
dc.contributor.authorZhao, Yanyun
dc.contributor.authorAugustin, Jan Lukas
dc.contributor.authorJeon, Eui-Ik
dc.contributor.authorLee, Impyeong
dc.contributor.authorZedda, Luca
dc.contributor.authorLoddo, Andrea
dc.contributor.authorDi Ruberto, Cecilia
dc.contributor.authorVerma, Sagar
dc.contributor.authorGupta, Siddharth
dc.contributor.authorMuralidhara, Shishir
dc.contributor.authorHegde, Niharika
dc.contributor.authorXing, Daitao
dc.contributor.authorEvangeliou, Nikolaos
dc.contributor.authorTzes, Anthony
dc.contributor.authorBartl, Vojtech
dc.contributor.authorSpanhel, Jakub
dc.contributor.authorHerout, Adam
dc.contributor.authorBhowmik, Neelanjan
dc.contributor.authorBreckon, Toby P.
dc.contributor.authorKundargi, Shivanand
dc.contributor.authorAnvekar, Tejas
dc.contributor.authorTabib, Ramesh Ashok
dc.contributor.authorMudengudi, Uma
dc.contributor.authorVats, Arpita
dc.contributor.authorSong, Yang
dc.contributor.authorLiu, Delong
dc.contributor.authorLi, Yonglin
dc.contributor.authorLi, Shuman
dc.contributor.authorTan, Chenhao
dc.contributor.authorLan, Long
dc.contributor.authorSomers, Vladimir
dc.contributor.authorDe Vleeschouwer, Christophe
dc.contributor.authorAlahi, Alexandre
dc.contributor.authorHuang, Hsiang-Wei
dc.contributor.authorYang, Cheng-Yen
dc.contributor.authorHwang, Jenq-Neng
dc.contributor.authorKim, Pyong-Kun
dc.contributor.authorKim, Kwangju
dc.contributor.authorLee, Kyoungoh
dc.contributor.authorJiang, Shuai
dc.contributor.authorLi, Haiwen
dc.contributor.authorZiqiang, Zheng
dc.contributor.authorVu, Tuan-Anh
dc.contributor.authorNguyen-Truong, Hai
dc.contributor.authorYeung, Sai-Kit
dc.contributor.authorJia, Zhuang
dc.contributor.authorYang, Sophia
dc.contributor.authorHsu, Chih-Chung
dc.contributor.authorHou, Xiu-Yu
dc.contributor.authorJhang, Yu-An
dc.contributor.authorYang, Simon
dc.contributor.authorYang, Mau-Tsuen
dc.date.accessioned2023-09-07T07:08:54Z
dc.date.available2023-09-07T07:08:54Z
dc.date.issued2023
dc.identifier.citationKiefer, 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 <i>WACVW 2023 : IEEE/CVF Winter Conference on Applications of Computer Vision Workshops</i> (pp. 265-302). IEEE. Proceedings (IEEE Winter Conference on Applications of Computer Vision Workshops). <a href="https://doi.org/10.1109/wacvw58289.2023.00033" target="_blank">https://doi.org/10.1109/wacvw58289.2023.00033</a>
dc.identifier.otherCONVID_176862364
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/88935
dc.description.abstractThe 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).en
dc.format.extent724
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofWACVW 2023 : IEEE/CVF Winter Conference on Applications of Computer Vision Workshops
dc.relation.ispartofseriesProceedings (IEEE Winter Conference on Applications of Computer Vision Workshops)
dc.rightsIn Copyright
dc.subject.othertraining
dc.subject.othercomputer vision
dc.subject.otherconferences
dc.subject.otherobject detection
dc.subject.otherdetectors
dc.subject.otherbenchmark testing
dc.subject.otherautonomous aerial vehicles
dc.title1st Workshop on Maritime Computer Vision (MaCVi) 2023 : Challenge Results
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-202309074968
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.relation.isbn979-8-3503-2057-2
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange265-302
dc.relation.issn2572-4398
dc.type.versionacceptedVersion
dc.rights.copyright© 2023 IEEE
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceIEEE Winter Applications and Computer Vision Workshops
dc.subject.ysoilmaisimet
dc.subject.ysokonferenssit
dc.subject.ysomeriliikenne
dc.subject.ysokonenäkö
dc.subject.ysoitseohjautuvat laivat
dc.subject.ysobenchmarking
dc.subject.ysomiehittämättömät ilma-alukset
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p4220
jyx.subject.urihttp://www.yso.fi/onto/yso/p38203
jyx.subject.urihttp://www.yso.fi/onto/yso/p2046
jyx.subject.urihttp://www.yso.fi/onto/yso/p2618
jyx.subject.urihttp://www.yso.fi/onto/yso/p38329
jyx.subject.urihttp://www.yso.fi/onto/yso/p9747
jyx.subject.urihttp://www.yso.fi/onto/yso/p24149
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1109/wacvw58289.2023.00033
jyx.fundinginformationThis 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.
dc.type.okmA4


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