Vision Skills Needed to Answer Visual Questions
October 07, 2020 ยท Declared Dead ยท ๐ Proc. ACM Hum. Comput. Interact.
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Authors
Xiaoyu Zeng, Yanan Wang, Tai-Yin Chiu, Nilavra Bhattacharya, Danna Gurari
arXiv ID
2010.03160
Category
cs.HC: Human-Computer Interaction
Citations
26
Venue
Proc. ACM Hum. Comput. Interact.
Last Checked
3 months ago
Abstract
The task of answering questions about images has garnered attention as a practical service for assisting populations with visual impairments as well as a visual Turing test for the artificial intelligence community. Our first aim is to identify the common vision skills needed for both scenarios. To do so, we analyze the need for four vision skills---object recognition, text recognition, color recognition, and counting---on over 27,000 visual questions from two datasets representing both scenarios. We next quantify the difficulty of these skills for both humans and computers on both datasets. Finally, we propose a novel task of predicting what vision skills are needed to answer a question about an image. Our results reveal (mis)matches between aims of real users of such services and the focus of the AI community. We conclude with a discussion about future directions for addressing the visual question answering task.
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