FunQA: Towards Surprising Video Comprehension

Version 1.0
Xie, Binzhu; Zhang, Sicheng; Zhou, Zitang; Li, Bo; Zhang, Yuanhan; Hessel, Jack; Yang, Jingkang; Liu, Ziwei, 2024, "FunQA: Towards Surprising Video Comprehension", https://doi.org/10.21979/N9/SMR703, DR-NTU (Data), V1
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Description
Surprising videos, e.g., funny clips, creative performances, or visual illusions, attract significant attention. Enjoyment of these videos is not simply a response to visual stimuli; rather, it hinges on the human capacity to understand (and appreciate) commonsense violations depicted in these videos. We introduce FunQA, a challenging video question answering (QA) dataset specifically designed to evaluate and enhance the depth of video reasoning based on counter-intuitive and fun videos. Unlike most video QA benchmarks which focus on less surprising contexts, e.g., cooking or instructional videos, FunQA covers three previously unexplored types of surprising videos: 1) HumorQA , 2) CreativeQA, and 3) MagicQA. For each subset, we establish rigorous QA tasks designed to assess the model's capability in counter-intuitive timestamp localization, detailed video description, and reasoning around counter-intuitiveness. We also pose higher-level tasks, such as attributing a fitting and vivid title to the video, and scoring the video creativity. In total, the FunQA benchmark consists of 312K free-text QA pairs derived from 4.3K video clips, spanning a total of 24 video hours. Extensive experiments with existing VideoQA models reveal significant performance gaps for the FunQA videos across spatial-temporal reasoning, visual-centered reasoning, and free-text generation.
Subject Computer and Information Science
Keyword Video Understanding
Related Publication Xie, B., Zhang, S., Zhou, Z., Li, B., Zhang, Y., Hessel, J., ... & Liu, Z. (2023). Funqa: Towards surprising video comprehension. arXiv preprint arXiv:2306.14899. arXiv: 2306.14899v2
Funding Information
Ministry of Education (MOE): under its MOE AcRF Tier 2 (MOE-T2EP20221- 0012)
Nanyang Technological University: NTU NAP
RIE2020 Industry Alignment Fund– Industry Collaboration Projects (IAF-ICP) Funding Initiative
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