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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 15969naa a2202449 4500 | |
| 001 | oai:DiVA.org:liu-169305 | |
| 003 | SwePub | |
| 008 | 200912s2019 | |||||||||||000 ||eng| | |
| 024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1693052 URI |
| 024 | 7 | a https://doi.org/10.1109/ICCVW.2019.002762 DOI |
| 040 | a (SwePub)liu | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a ref2 swepub-contenttype |
| 072 | 7 | a kon2 swepub-publicationtype |
| 100 | 1 | a Kristanl, Mateju Univ Ljubljana, Slovenia4 aut |
| 245 | 1 0 | a The Seventh Visual Object Tracking VOT2019 Challenge Results |
| 264 | 1 | b IEEE COMPUTER SOC,c 2019 |
| 338 | a electronic2 rdacarrier | |
| 500 | a Funding Agencies|Slovenian research agencySlovenian Research Agency - Slovenia [J2-8175, P2-0214, P2-0094]; Czech Science Foundation Project GACR [P103/12/G084]; MURI project - MoD/DstlMURI; EPSRCEngineering & Physical Sciences Research Council (EPSRC) [EP/N019415/1]; WASP; VR (ELLIIT, LAST, and NCNN); SSF (SymbiCloud); AIT Strategic Research Programme; Faculty of Computer Science, University of Ljubljana, Slovenia | |
| 520 | a The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1). | |
| 650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datorseende och robotik0 (SwePub)102072 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Vision and Robotics0 (SwePub)102072 hsv//eng |
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| 700 | 1 | a Memarrnoghadam, Alirezau Univ Isfahan, Iran4 aut |
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| 700 | 1 | a Zhang, Baopengu Beijing Jiaotong Univ, Peoples R China4 aut |
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| 700 | 1 | a Li, Biu Chinese Acad Sci, Peoples R China; Huazhong Univ Sci & Technol, Peoples R China4 aut |
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| 700 | 1 | a Bai, Bingu Didi Chuxing, Peoples R China4 aut |
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| 700 | 1 | a Li, Bou SenseTime, Peoples R China4 aut |
| 700 | 1 | a Kim, Bycong Haku Hanwha Syst Co, South Korea; Kyungpook Natl Univ, South Korea4 aut |
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| 700 | 1 | a Qian, Chenu SenseTime, Peoples R China4 aut |
| 700 | 1 | a Chen, Chengu Peking Univ, Peoples R China4 aut |
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| 700 | 1 | a Zhang, Chunhuiu Chinese Acad Sci, Peoples R China4 aut |
| 700 | 1 | a Tao, Dachengu Univ Sydney, Australia4 aut |
| 700 | 1 | a Gupta, Deepaku Univ Amsterdam, Netherlands4 aut |
| 700 | 1 | a Song, Dejiau Huazhong Univ Sci & Technol, Peoples R China4 aut |
| 700 | 1 | a Wang, Dongu Dalian Univ Technol, Peoples R China4 aut |
| 700 | 1 | a Gavves, Efstratiosu Univ Amsterdam, Netherlands4 aut |
| 700 | 1 | a Yi, Eunuu Hanwha Syst Co, South Korea4 aut |
| 700 | 1 | a Khan, Fahad Shahbaz,d 1983-u Linköpings universitet,Datorseende,Tekniska fakulteten,Inception Inst Artificial Intelligence, U Arab Emirates4 aut0 (Swepub:liu)fahkh30 |
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| 700 | 1 | a Wang, Feiu SenseTime, Peoples R China4 aut |
| 700 | 1 | a Zhao, Feiu Chinese Acad Sci, Peoples R China4 aut |
| 700 | 1 | a De Ath, Georgeu Univ Exeter, England4 aut |
| 700 | 1 | a Bhat, Goutamu Swiss Fed Inst Technol, Switzerland4 aut |
| 700 | 1 | a Chen, Guanqiu SenseTime, Peoples R China4 aut |
| 700 | 1 | a Wang, Guangtingu Univ Sci & Technol China, Peoples R China4 aut |
| 700 | 1 | a Li, Guoxuanu SenseTime, Peoples R China4 aut |
| 700 | 1 | a Cevikalp, Hakanu Eskisehir Osmangazi Univ, Turkey4 aut |
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| 700 | 1 | a Saribas, Hasanu Eskisehir Tech Univ, Turkey4 aut |
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| 700 | 1 | a Yu, Hongyuanu Chinese Acad Sci, Peoples R China; Microsoft Res, Peoples R China4 aut |
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| 700 | 1 | a Lu, Huchuanu Dalian Univ Technol, Peoples R China4 aut |
| 700 | 1 | a Li, Huiu Jiangnan Univ, Peoples R China4 aut |
| 700 | 1 | a Li, Jiakunu Beijing Jiaotong Univ, Peoples R China4 aut |
| 700 | 1 | a Li, Jianhuu Dalian Univ Technol, Peoples R China4 aut |
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| 700 | 1 | a Chen, Jieu Xidian Univ, Peoples R China4 aut |
| 700 | 1 | a Gao, Jieu Xidian Univ, Peoples R China4 aut |
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| 700 | 1 | a Tang, Jinu Anhui Univ, Peoples R China4 aut |
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| 700 | 1 | a Zhang, Yunhuau Dalian Univ Technol, Peoples R China4 aut |
| 700 | 1 | a Li, Yunkunu Jiangnan Univ, Peoples R China4 aut |
| 700 | 1 | a Luo, Zeyu Wang Zhaou Chinese Acad Sci, Peoples R China4 aut |
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| 700 | 1 | a Feng, Zhen-Huau Univ Surrey, England4 aut |
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| 700 | 1 | a Xiong, Zhiweiu Univ Sci & Technol China, Peoples R China4 aut |
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| 710 | 2 | a Univ Ljubljana, Sloveniab Czech Tech Univ, Czech Republic4 org |
| 773 | 0 | t 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW)d : IEEE COMPUTER SOCg , s. 2206-2241q <2206-2241z 9781728150239 |
| 856 | 4 | u https://liu.diva-portal.org/smash/get/diva2:1466584/FULLTEXT01.pdfx primaryx Raw objecty fulltext:postprint |
| 856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-169305 |
| 856 | 4 8 | u https://doi.org/10.1109/ICCVW.2019.00276 |
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