Modernizing Old Photos Using Multiple References via Photorealistic Style Transfer
Agus Gunawan, Soo Ye Kim, Hyeonjun Sim, Jae-Ho Lee, Munchurl Kim

TL;DR
This paper introduces a novel multi-reference framework for old photo modernization that combines photorealistic style transfer and enhancement, trained on synthetic data, and evaluated on a new benchmark dataset, outperforming existing methods.
Contribution
The paper proposes MROPM-Net and a synthetic data scheme for effective multi-reference old photo modernization, including a new benchmark dataset and style selection for improved results.
Findings
Outperforms baseline methods in old photo modernization
Effectively utilizes multiple references for style transfer
Achieves high-quality results without using real old photos in training
Abstract
This paper firstly presents old photo modernization using multiple references by performing stylization and enhancement in a unified manner. In order to modernize old photos, we propose a novel multi-reference-based old photo modernization (MROPM) framework consisting of a network MROPM-Net and a novel synthetic data generation scheme. MROPM-Net stylizes old photos using multiple references via photorealistic style transfer (PST) and further enhances the results to produce modern-looking images. Meanwhile, the synthetic data generation scheme trains the network to effectively utilize multiple references to perform modernization. To evaluate the performance, we propose a new old photos benchmark dataset (CHD) consisting of diverse natural indoor and outdoor scenes. Extensive experiments show that the proposed method outperforms other baselines in performing modernization on real old…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGenerative Adversarial Networks and Image Synthesis · Image Enhancement Techniques · Advanced Image and Video Retrieval Techniques
