# Perceptually Motivated Method for Image Inpainting Comparison

arXiv: https://arxiv.org/abs/1907.06296 · HTML: https://mlsanity.com/paper/1907.06296/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jul 2019.

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

- [Deep Two-Stage High-Resolution Image Inpainting](https://mlsanity.com/paper/2104.13464/) (2021)

## Abstract (arXiv)

The field of automatic image inpainting has progressed rapidly in recent years, but no one has yet proposed a standard method of evaluating algorithms. This absence is due to the problem's challenging nature: image-inpainting algorithms strive for realism in the resulting images, but realism is a subjective concept intrinsic to human perception. Existing objective image-quality metrics provide a poor approximation of what humans consider more or less realistic. To improve the situation and to better organize both prior and future research in this field, we conducted a subjective comparison of nine state-of-the-art inpainting algorithms and propose objective quality metrics that exhibit high correlation with the results of our comparison.