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

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Back, Seung-Yeon, Son, Geonho, Jeong, Dahye, Park, Eunil, Woo, Simon S.
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866909346851454976
author Back, Seung-Yeon
Son, Geonho
Jeong, Dahye
Park, Eunil
Woo, Simon S.
author_facet Back, Seung-Yeon
Son, Geonho
Jeong, Dahye
Park, Eunil
Woo, Simon S.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2410_09529
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Preserving Old Memories in Vivid Detail: Human-Interactive Photo Restoration Framework
Back, Seung-Yeon
Son, Geonho
Jeong, Dahye
Park, Eunil
Woo, Simon S.
Computer Vision and Pattern Recognition
Artificial Intelligence
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.
title Preserving Old Memories in Vivid Detail: Human-Interactive Photo Restoration Framework
topic Computer Vision and Pattern Recognition
Artificial Intelligence
url https://arxiv.org/abs/2410.09529