用AI自动化修复老照片，支持多阶段精准处理损伤
Preserving Old Memories in Vivid Detail: Human-Interactive Photo Restoration Framework
- 分阶段设计修复流程，针对不同损伤类型优化处理
- 构建首个公开老照片修复数据集，填补领域评估空白
- 兼顾自动化与交互性，适合家庭用户与影像修复从业者
照片修复技术有助于保存视觉记忆。然而，实体照片易受各种退化影响，包括物理损伤和画质下降等。尽管人工专家修复可提升质量，但成本高、耗时长。本文提出一种基于AI的多阶段照片修复框架，每阶段专门应对特定类型的图片损伤，加速并实现修复过程的自动化。通过将各项技术整合至统一架构，该框架旨在提供一站式老照片修复解决方案。此外，为支持评估，我们构建了一个全新的老照片修复数据集。
原文摘要 · Abstract (English)
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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