Workshop on Multi-modal Video Analysis and Moments in Time Challenge Call for Papers
1st CALL FOR PAPERS
Workshop on Multi-modal Video Analysis and Moments in Time Challenge
Nov. 2, 2019 | Seoul, Korea, in conjunction with ICCV 2019
July 31, 2019 : Paper submission deadline
August 14, 2019 : Notification to authors
August 20, 2019: Camera-ready paper deadline
Video understanding is a very active research area in the computer
vision community. This workshop aims to particularly focus on
modeling, understanding, and leveraging the multi-modal nature of
video. Recent research has amply demonstrated that in many scenarios
multimodal video analysis is much richer than analysis based on any
single modality. At the same time, multimodal analysis poses many
challenges not encountered in modeling single modalities for
understanding of videos (for e.g. building complex models that can
fuse spatial, temporal, and auditory information). The workshop will
be focused on video analysis/understanding related, but not limited,
to the following topics:
- deep network architectures for multimodal learning.
- multimodal unsupervised or weakly supervised learning from video.
- multimodal emotion/affect modeling in video.
- multimodal action/scene recognition in video.
- multimodal video analysis applications including but not limited to
sports video understanding, entertainment video understanding,
- multimodal embodied perception for vision (e.g. modeling touch and video).
- multimodal video understanding datasets and benchmarks.
Papers should be limited to four pages, including figures and tables,
in the ICCV style and will not be archived in the conference
proceedings. We highly appreciate short forms of full papers accepted
at ICCV as well as unpublished ideas and concept papers. Please note
that papers in this workshop, as they will not be published in any
proceedings and do not count as publications, can still be submitted
to next year's CVPR.
Dhiraj Joshi, IBM Research AI
Mathew Monfort, MIT CSAIL
Kandan Ramakrishnan, MIT CSAIL
Rogerio Schmidt Feris, IBM Research AI
David Harwath, MIT CSAIL
Dan Gutfreund, IBM Research AI
Carl Vondrick, Columbia University
Bolei Zhou, CUHK
Hang Zhou, MIT CSAIL
Zhicheng Yan, Facebook
Aude Oliva, MIT CSAIL
On behalf of the organizers,
MIT-IBM Watson Lab