Bias in Automated Image Colorization: Metrics and Error Types

• URL: http://arxiv.org/abs/2202.08143v1
• Date: Wed, 16 Feb 2022 15:34:09 GMT
• Title: Bias in Automated Image Colorization: Metrics and Error Types
• Authors: Frank Stapel, Floris Weers, Doina Bucur
• Abstract summary: We measure the color shifts present in colorized images from the ADE20K dataset, when colorized by the automatic GAN-based DeOldify model. We introduce fine-grained local and regional bias measurements between the original and the colorized images, and observe many colorization effects.
• Score: 0.5801044612920815
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: We measure the color shifts present in colorized images from the ADE20K dataset, when colorized by the automatic GAN-based DeOldify model. We introduce fine-grained local and regional bias measurements between the original and the colorized images, and observe many colorization effects. We confirm a general desaturation effect, and also provide novel observations: a shift towards the training average, a pervasive blue shift, different color shifts among image categories, and a manual categorization of colorization errors in three classes.

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