  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 photos, even though no old
photos were used during training. Moreover, our method can appropriately select
styles from multiple references for each semantic region in the old photo to
further improve the modernization performance.
