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Title: Multiple Hypothesis Video Relation Detection
Authors: Donglin Di
Xindi Shang 
Weinan Zhang
Xun Yang 
Tat-Seng Chua 
Keywords: Relational association
Video relation detection
Visual relationship
Issue Date: 11-Sep-2019
Citation: Donglin Di, Xindi Shang, Weinan Zhang, Xun Yang, Tat-Seng Chua (2019-09-11). Multiple Hypothesis Video Relation Detection. BigMM 2019 : 287-291. ScholarBank@NUS Repository.
Abstract: Video relation in the form of triplet (subject, predicate, object) plays a vital role in video content understanding. Existing works on video relation detection are limited to associating short-term relations into long-term relations throughout the video, because of the inaccurate and missing problem of short-term proposals. To alleviate the weakness of existing video relation detection methods, this work proposes a novel approach called Multi-Hypothesis Relational Association (MHRA), that can generate multiple hypotheses for video relation instances for more robust long-term relation prediction. Experiments on the benchmark dataset show that MHRA is able to outperform the state-of-the-art methods. © 2019 IEEE.
Source Title: BigMM 2019
ISBN: 9781728155272
DOI: 10.1109/BigMM.2019.000-9
Appears in Collections:Staff Publications

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