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Yu-Gang Jiang
Professor School of Computer Science Fudan University Shanghai ygj AT fudan.edu.cn |
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My research is in the areas of multimedia content analysis and computer vision. I lead the BigVid Lab, conducting research on all aspects of extracting high-level information from big video data, such as video event recognition, object/scene recognition and large-scale visual search. I participate regularly in international benchmark competitions. At the annual U.S. NIST TREC video retrieval evaluation (TRECVID), I have designed a few best-performing systems (among many submissions worldwide) in 2008 video concept detection task and 2010 multimedia event detection task. I am also one of the organizers of the THUMOS Challenge on Large Scale Action Recognition.My publications and citations on Google Scholar can be found here. |
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[06/2016] NEW! Our work on image search with hash codes received the 2016 IEEE Trans. on Multimedia Prize Paper Award Honorable Mention.
[02/2016] Due to many requests, researchers interested in getting the videos of the CCV dataset can fill up this form and send to me for a link. [02/2015] We have released FCVID, one of the largest public Web video datasets with manual annotations (91,223 videos, 239 categories). [11/2014] Our paper received best poster award at ACM Multimedia 2014. [08/2014] The website of ACM ICMR 2015 (June 23-26, Shanghai, China) is online. [08/2014] We have released VCDB, the largest public dataset with manually annotated real partial video copies. [08/2014] The workshop of the 2nd THUMOS Action Recognition Challenge will be held in conjunction with ECCV 2014. [01/2014] The violent scenes detection dataset used in MediaEval 2013 is available online, jointly provided by Technicolor, Fudan, and UIT Vietnam. |
dataset / code
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FCVID: Fudan-Columbia Video Dataset 91,223 Web videos annotated manually according to 239 categories |
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VCDB: a large-scale database for partial copy detection in videos ECCV 2014 paper |
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Dataset for predicting video emotions AAAI 2014 paper |
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Dataset for predicting video interestingness AAAI 2013 paper |
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Part-level attributes for visual recognition (source code) ECCV 2012 paper |
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CCV: a benchmark dataset for consumer video analysis Note: To obtain a copy of the videos in CCV, please fill up this form and send to me for a link. |
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Domain adaptive semantic diffusion (DASD) for context-based visual annotation refinement ICCV 2009 paper | source code |
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VIREO-374: keypoint-based LSCOM semantic concept detectors
see who has used it CU-VIREO374: fusing Columbia374 and VIREO374 for large scale semantic concept detection see who has used it |
Selected other recent projects
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Query-adaptive image search with hash codes
IEEE TMM 2013 paper |
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Violent scene detection in movies |
Mailing Address: Room 413-5, Computer Science Building, 825 Zhangheng Road, Pudong, Shanghai 201203, China. Tel: +86-21-51355532
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