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Computer Vision Datasets and Models Exhibit Cultural and Linguistic Diversity in Perception
March 12, 2024, 4:49 a.m. | Andre Ye, Sebastin Santy, Jena D. Hwang, Amy X. Zhang, Ranjay Krishna
cs.CV updates on arXiv.org arxiv.org
Abstract: Computer vision often treats human perception as homogeneous: an implicit assumption that visual stimuli are perceived similarly by everyone. This assumption is reflected in the way researchers collect datasets and train vision models. By contrast, literature in cross-cultural psychology and linguistics has provided evidence that people from different cultural backgrounds observe vastly different concepts even when viewing the same visual stimuli. In this paper, we study how these differences manifest themselves in vision-language datasets and …
abstract arxiv computer computer vision computer vision datasets contrast cs.cl cs.cv cs.cy cs.hc datasets diversity human linguistics literature perception psychology researchers the way train type vision vision models visual
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