Synopses of Movie Narratives: a Video-Language Dataset for Story
Understanding
- URL: http://arxiv.org/abs/2203.05711v4
- Date: Wed, 5 Apr 2023 02:09:02 GMT
- Title: Synopses of Movie Narratives: a Video-Language Dataset for Story
Understanding
- Authors: Yidan Sun, Qin Chao, Yangfeng Ji and Boyang Li
- Abstract summary: We release a video-language story dataset, Synopses of Movie Narratives (SyMoN), containing 5,193 video summaries of popular movies and TV series with a total length of 869 hours.
SyMoN captures naturalistic storytelling videos made by human creators and intended for a human audience.
- Score: 13.52545041750095
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Despite recent advances of AI, story understanding remains an open and
under-investigated problem. We collect, preprocess, and publicly release a
video-language story dataset, Synopses of Movie Narratives (SyMoN), containing
5,193 video summaries of popular movies and TV series with a total length of
869 hours. SyMoN captures naturalistic storytelling videos made by human
creators and intended for a human audience. As a prototypical and naturalistic
story dataset, SyMoN features high coverage of multimodal story events and
abundant mental-state descriptions. Its use of storytelling techniques cause
cross-domain semantic gaps that provide appropriate challenges to existing
models. We establish benchmarks on video-text retrieval and zero-shot alignment
on movie summary videos, which showcase the importance of in-domain data and
long-term memory in story understanding. With SyMoN, we hope to lay the
groundwork for progress in multimodal story understanding.
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