# Color: A Crucial Factor for Aesthetic Quality Assessment in a Subjective Dataset of Paintings

arXiv: https://arxiv.org/abs/1609.05583 · HTML: https://mlsanity.com/paper/1609.05583/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2016.

## Built on by (most cited first, 4 of 4)

- [APDDv2: Aesthetics of Paintings and Drawings Dataset with Artist Labeled Scores and Comments](https://mlsanity.com/paper/2411.08545/) (2024)
- [Paintings and Drawings Aesthetics Assessment with Rich Attributes for Various Artistic Categories](https://mlsanity.com/paper/2405.02982/) (2024)
- [PPJudge: Towards Human-Aligned Assessment of Artistic Painting Process](https://mlsanity.com/paper/2507.09242/) (2025)
- [MPJudge: Towards Perceptual Assessment of Music-Induced Paintings](https://mlsanity.com/paper/2511.07137/) (2025)

## Abstract (arXiv)

Computational aesthetics is an emerging field of research which has attracted different research groups in the last few years. In this field, one of the main approaches to evaluate the aesthetic quality of paintings and photographs is a feature-based approach. Among the different features proposed to reach this goal, color plays an import role. In this paper, we introduce a novel dataset that consists of paintings of Western provenance from 36 well-known painters from the 15th to the 20th century. As a first step and to assess this dataset, using a classifier, we investigate the correlation between the subjective scores and two widely used features that are related to color perception and in different aesthetic quality assessment approaches. Results show a classification rate of up to 73% between the color features and the subjective scores.