  Heterogeneous face recognition (HFR) refers to matching face imagery across
different domains. It has received much interest from the research community as
a result of its profound implications in law enforcement. A wide variety of new
invariant features, cross-modality matching models and heterogeneous datasets
being established in recent years. This survey provides a comprehensive review
of established techniques and recent developments in HFR. Moreover, we offer a
detailed account of datasets and benchmarks commonly used for evaluation. We
finish by assessing the state of the field and discussing promising directions
for future research.

Computer Vision and Pattern Recognition