  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.
