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MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
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Proceedings of the 6th ACM international conference on Image and video retrieval
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Information Retrieval
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Proceedings of the 15th international conference on Multimedia
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Transfer learning from multiple source domains via consensus regularization
Proceedings of the 17th ACM conference on Information and knowledge management
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IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Hybrid active learning for cross-domain video concept detection
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Discriminative fields for modeling semantic concepts in video
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
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CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Cross-domain video concept detection: A joint discriminative and generative active learning approach
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Multi-modal distance metric learning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Many research groups worldwide are now investigating techniques which can support information retrieval on archives of digital video and as groups move on to implement these techniques they inevitably try to evaluate the performance of their techniques in practical situations. The difficulty with doing this is that there is no test collection or any environment in which the effectiveness of video IR or video IR sub-tasks, can be evaluated and compared. The annual series of TREC exercises has, for over a decade, been benchmarking the effectiveness of systems in carrying out various information retrieval tasks on text and audio and has contributed to a huge improvement in many of these. Two years ago, a track was introduced which covers shot boundary detection, feature extraction and searching through archives of digital video. In this paper we present a summary of the activities in the TREC Video track in 2002 where 17 teams from across the world took part.