Realistic Saliency Guided Image Enhancement

Common editing operations performed by professional photographers include the cleanup operations: de-emphasizing distracting elements and enhancing subjects. These edits are challenging, requiring a delicate balance between manipulating the viewer's attention while maintaining photo realism. Wh...

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Bibliographic Details
Published inProceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 186 - 194
Main Authors Miangoleh, S. Mahdi H., Bylinskii, Zoya, Kee, Eric, Shechtman, Eli, Aksoy, Yagiz
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2023
Subjects
Attenuation
Computational imaging
Computer vision
Image enhancement
Memory management
Pattern recognition
Runtime
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Summary:Common editing operations performed by professional photographers include the cleanup operations: de-emphasizing distracting elements and enhancing subjects. These edits are challenging, requiring a delicate balance between manipulating the viewer's attention while maintaining photo realism. While recent approaches can boast successful examples of attention attenuation or amplification, most of them also suffer from frequent unrealistic edits. We propose a realism loss for saliency-guided image enhancement to maintain high realism across varying image types, while attenuating distractors and amplifying objects of interest. Evaluations with professional photographers confirm that we achieve the dual objective of realism and effectiveness, and outperform the recent approaches on their own datasets, while requiring a smaller memory footprint and runtime. We thus offer a viable solution for automating image enhancement and photo cleanup operations.
ISSN:1063-6919
DOI:10.1109/CVPR52729.2023.00026