Heterogeneous face synthesis aims at generating visually realistic and identity-preserving portraits of different modality,such as sketches,caricatures,etc.Heterogeneous face synthesis is of great significance for both public security and digital entertainment,and has attracted numerous attention.Recently,inspired by the dramatic progress in generative adversarial networks (GANs) and their great successes in image-to-image translation tasks,researchers have proposed a number of new heterogeneous face synthesis methods based on GANs.In this paper,we briefly introduce the development of heterogeneous face synthesis,and detailed recent progresses in terms of developments of applications,architectures of GANs,performance evaluation approaches,datasets,and qualitative analysis.Finally,we summarize the challenges and some prospects of heterogeneous face synthesis.