Cross-domain image retrieval: methods and applications

Cross-domain images have been witnessed in an increasing number of applications. This new trend triggers demands for cross-domain image retrieval (CDIR), which finds images in one visual domain according to a query image from another visual domain. Although image retrieval has been studied extensively, exploration of the CDIR remains at its initial stage. This study systematically surveys the methods and applications of the CDIR. Since images from different visual domains exhibit different features, learning discriminative feature representations while preserving domain-invariant features of images from different visual domains is the main challenge of the CDIR. According to the feature transformation stage of images from different visual domains, existing CDIR methods are categorized and analyzed. One is based on feature space migration and the other is based on image domain migration. Then, applications of CDIR in clothing, infrared, remote sensing, sketch, and other scenarios are summarized. Finally, the existing CDIR schemes are concluded, and new directions for future research are proposed.