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https://doi.org/10.1109/BigMM.2019.000-9
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. https://doi.org/10.1109/BigMM.2019.000-9 | 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 | URI: | https://scholarbank.nus.edu.sg/handle/10635/167707 | ISBN: | 9781728155272 | DOI: | 10.1109/BigMM.2019.000-9 |
Appears in Collections: | Staff Publications Elements |
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