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FunQA: Towards Surprising Video Comprehension
March 25, 2024, 4:45 a.m. | Binzhu Xie, Sicheng Zhang, Zitang Zhou, Bo Li, Yuanhan Zhang, Jack Hessel, Jingkang Yang, Ziwei Liu
cs.CV updates on arXiv.org arxiv.org
Abstract: Surprising videos, such as 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 …
abstract arxiv attention capacity creative cs.ai cs.cl cs.cv cs.mm funny human performances question type video videos visual
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