# Bias in Automated Image Colorization: Metrics and Error Types

arXiv: https://arxiv.org/abs/2202.08143 · HTML: https://mlsanity.com/paper/2202.08143/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 20 references that are in the map.
- First posted on arXiv 16 Feb 2022.

## Builds on (most cited first, 10 of 10)

- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Colorful Image Colorization](https://mlsanity.com/paper/1603.08511/) (2016)
- [Learning Representations for Automatic Colorization](https://mlsanity.com/paper/1603.06668/) (2016)
- [Instance-aware Image Colorization](https://mlsanity.com/paper/2005.10825/) (2020)
- [Deep Colorization](https://mlsanity.com/paper/1605.00075/) (2016)
- [ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution](https://mlsanity.com/paper/1907.09837/) (2019)
- [Towards Vivid and Diverse Image Colorization with Generative Color Prior](https://mlsanity.com/paper/2108.08826/) (2021)
- [Learning Diverse Image Colorization](https://mlsanity.com/paper/1612.01958/) (2016)
- [Image Colorization with Generative Adversarial Networks](https://mlsanity.com/paper/1803.05400/) (2018)
- [Image Colorization By Capsule Networks](https://mlsanity.com/paper/1908.08307/) (2019)

## Built on by (most cited first, 1 of 1)

- [LatentColorization: Latent Diffusion-Based Speaker Video Colorization](https://mlsanity.com/paper/2405.05707/) (2024)

## Abstract (arXiv)

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.