Please use this identifier to cite or link to this item: https://doi.org/10.1145/3343031.3356082
Title: Relation Understanding in Videos: A Grand Challenge Overview
Authors: Xindi Shang 
Junbin Xiao
Donglin Di
Tat-Seng Chua 
Keywords: video content analysis
visual relation
object detection
action recognition
spatio-temporal
Issue Date: 21-Oct-2019
Publisher: Association for Computing Machinery, Inc
Citation: Xindi Shang, Junbin Xiao, Donglin Di, Tat-Seng Chua (2019-10-21). Relation Understanding in Videos: A Grand Challenge Overview. ACM Multimedia 2019 : 2652 - 2656. ScholarBank@NUS Repository. https://doi.org/10.1145/3343031.3356082
Abstract: ACM Multimedia 2019 Video Relation Understanding Challenge is the first grand challenge aiming at pushing video content analysis at the relational and structural level. This year, the challenge asks the participants to explore and develop innovative algorithms to detect object entities and their relations based on a large-scale user-generated video dataset. The tasks will advance the foundation of future visual systems that are able to perform complex inferences. This paper presents an overview of the grand challenge, including background, detailed descriptions of the three proposed tasks, the corresponding datasets for training, validation and testing, and the evaluation process. © 2019 Association for Computing Machinery. ACM ISBN 978-1-4503-6889-6/19/10...$15.00
Source Title: ACM Multimedia 2019
URI: https://scholarbank.nus.edu.sg/handle/10635/168419
ISBN: 9.78E+12
DOI: 10.1145/3343031.3356082
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