Coview'18: The 1st workshop and challenge on comprehensive video understanding in the wild

Kwanghoon Sohn, Jongwoo Lim, Ming Hsuan Yang, Jison Hsu, Hyeran Byun, Stephen Lin, Euntai Kim, Seungryong Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The 1st Workshop and Challenge on Comprehensive Video Understanding in the Wild, dubbed CoVieW'18, is held in Seoul, Korea on October 22, 2018, in conjuction with ACM Multimedia 2018. The workshop aims to solve the joint and comprehensive understanding problem in untrimmed videos with a particular emphasis on joint action and scene recognition. The workshop encourages researchers to participate in joint action and scene recognition challenge in untrimmed videos and to report their results. The workshop program includes 1 keynote speech, 2 invited speakers, 6 regular and challenge papers. The developments made in the workshop will deliver a step change in a variety of video applications.

Original languageEnglish
Title of host publicationMM 2018 - Proceedings of the 2018 ACM Multimedia Conference
PublisherAssociation for Computing Machinery, Inc
Pages2113-2115
Number of pages3
ISBN (Electronic)9781450356657
DOIs
Publication statusPublished - 2018 Oct 15
Event26th ACM Multimedia conference, MM 2018 - Seoul, Korea, Republic of
Duration: 2018 Oct 222018 Oct 26

Publication series

NameMM 2018 - Proceedings of the 2018 ACM Multimedia Conference

Other

Other26th ACM Multimedia conference, MM 2018
CountryKorea, Republic of
CitySeoul
Period18/10/2218/10/26

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction

Cite this

Sohn, K., Lim, J., Yang, M. H., Hsu, J., Byun, H., Lin, S., Kim, E., & Kim, S. (2018). Coview'18: The 1st workshop and challenge on comprehensive video understanding in the wild. In MM 2018 - Proceedings of the 2018 ACM Multimedia Conference (pp. 2113-2115). (MM 2018 - Proceedings of the 2018 ACM Multimedia Conference). Association for Computing Machinery, Inc. https://doi.org/10.1145/3240508.3243720