TRECVID 2018: Benchmarking Video Activity Detection, Video Captioning and Matching, Video Storytelling Linking and Video Search

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George Awad, Asad A. Butt, Keith Curtis, Yooyoung Lee, Jonathan Fiscus, Afzal Godil, David Joy, Andrew Delgado, Alan F. Smeaton, Yvette Graham, Wessel Kraaij, Georges Qu?not, Joao Magalhaes, David Semedo, and Saverio Blasi, TRECVID 2018: Benchmarking Video Activity Detection, Video Captioning and Matching, Video Storytelling Linking and Video Search, Proceedings of TRECVID 2018, TRECVID 2018, Gaithersburg, MD, 2018, 1 - 38

Abstract

The TREC Video Retrieval Evaluation (TRECVID)2018 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in research and development of content-based exploitation and retrieval of information from digital video via open, metrics-based evaluation.Over the last eighteen years this effort has yielded abetter understanding of how systems can effectively accomplish such processing and how one can reliably benchmark their performance. TRECVID is funded by NIST (National Institute of Standards and Technology) and other US government agencies. In addition, many organizations and individuals worldwide contribute significant time and effort. TRECVID 2018 represented a continuation of three tasks from TRECVID 2017. In addition,three new pilot tasks: Social Media Video Story-telling Linking, Streaming Multimedia Knowledge-base Population, and Activities in Extended Videotask were introduced.

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Author's Homepage: http://people.tcd.ie/ygraham
Other Titles: Proceedings of TRECVID 2018
Type of material: Conference Paper