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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