mlsanityData to 13 Oct 2026

Multi-color balance for color constancy

arXiv 2105.10228 ↗First posted 21 May 2021cs.CVcited by 3

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Abstract (arXiv)

In this paper, we propose a novel multi-color balance adjustment for color constancy. The proposed method, called "n-color balancing," allows us not only to perfectly correct n target colors on the basis of corresponding ground truth colors but also to correct colors other than the n colors. In contrast, although white-balancing can perfectly adjust white, colors other than white are not considered in the framework of white-balancing in general. In an experiment, the proposed multi-color balancing is demonstrated to outperform both conventional white and multi-color balance adjustments including Bradford's model.

Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). Builds on 6 of its 30 references that are in the map. First posted on arXiv 21 May 2021.

Builds on

6 of 30 references.

References · 6

  1. 2020Deep White-Balance Editingcited by 54
  2. 2019What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performancecited by 37
  3. 2019Scene Segmentation-Based Luminance Adjustment for Multi-Exposure Image Fusioncited by 15
  4. 2020Fast Soft Color Segmentationcited by 13
  5. 2018Rehabilitating the ColorChecker Dataset for Illuminant Estimationcited by 7
  6. 2021Multi-color balancing for correctly adjusting the intensity of target colorscited by 3

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 1.

3 papers.