Preserving Old Memories in Vivid Detail: Human-Interactive Photo Restoration Framework

• URL: http://arxiv.org/abs/2410.09529v1
• Date: Sat, 12 Oct 2024 13:23:08 GMT
• Title: Preserving Old Memories in Vivid Detail: Human-Interactive Photo Restoration Framework
• Authors: Seung-Yeon Back, Geonho Son, Dahye Jeong, Eunil Park, Simon S. Woo,
• Abstract summary: Photo restoration can improve the quality of outcomes, but it often comes at a high price in terms of cost and time for restoration. We present the AI-based photo restoration framework composed of multiple stages, where each stage is tailored to enhance and restore specific types of photo damage. We present a novel old photo restoration dataset because we lack a publicly available dataset for our evaluation.
• Score: 19.213916633152625
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Photo restoration technology enables preserving visual memories in photographs. However, physical prints are vulnerable to various forms of deterioration, ranging from physical damage to loss of image quality, etc. While restoration by human experts can improve the quality of outcomes, it often comes at a high price in terms of cost and time for restoration. In this work, we present the AI-based photo restoration framework composed of multiple stages, where each stage is tailored to enhance and restore specific types of photo damage, accelerating and automating the photo restoration process. By integrating these techniques into a unified architecture, our framework aims to offer a one-stop solution for restoring old and deteriorated photographs. Furthermore, we present a novel old photo restoration dataset because we lack a publicly available dataset for our evaluation.

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