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Towards Better User Studies in Computer Graphics and Vision. (arXiv:2206.11461v1 [cs.GR])
Web: http://arxiv.org/abs/2206.11461
June 24, 2022, 1:12 a.m. | Zoya Bylinskii, Laura Herman, Aaron Hertzmann, Stefanie Hutka, Yile Zhang
cs.CV updates on arXiv.org arxiv.org
Online crowdsourcing platforms make it easy to perform evaluations of
algorithm outputs with surveys that ask questions like "which image is better,
A or B?") The proliferation of these "user studies" in vision and graphics
research papers has led to an increase of hastily conducted studies that are
sloppy and uninformative at best, and potentially harmful and misleading. We
argue that more attention needs to be paid to both the design and reporting of
user studies in computer vision and …
More from arxiv.org / cs.CV updates on arXiv.org
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