Realistic Saliency Guided Image Enhancement

• URL: http://arxiv.org/abs/2306.06092v1
• Date: Fri, 9 Jun 2023 17:52:34 GMT
• Title: Realistic Saliency Guided Image Enhancement
• Authors: S. Mahdi H. Miangoleh and Zoya Bylinskii and Eric Kee and Eli Shechtman and Ya\u{g}{\i}z Aksoy
• Abstract summary: Common editing operations performed by professional photographers include de-emphasizing distracting elements and enhancing subjects. We propose a realism loss for saliency-guided image enhancement to maintain high realism across varying image types. We outperform the recent approaches on their own datasets, while requiring a smaller memory footprint and runtime.
• Score: 32.446298454642985
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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