With recent advancements in deep learning, the capabilities of automatic face recognition has been significantly increased. However, face recognition in unconstrained environment with non-cooperative users is still a research challenge, pertinent for users such as law enforcement agencies. While several covariates such as pose, expression, illumination, aging, and low resolution have received significant attention, “disguise” is still considered an arduous covariate of face recognition. Disguise as a covariate involves both intentional and unintentional changes on a face through which one can either obfuscate his/her identity or impersonate someone else’s identity. The problem can be further exacerbated due to unconstrained environment or “in the wild” scenarios. However, disguise in the wild has not been studied in a comprehensive way, primarily due to unavailability of such as database. As part of the International Workshop on Disguised Face in the Wild at ICCV2019, a competition is being held in which participants are asked to show their results on the Disguised Faces in the Wild (DFW) 2019 database.

Researchers who submit to the competition are highly encouraged to submit their paper to the DFW Workshop@ICCV2019 as well!

Disguised Face Dataset

The DFW 2019 dataset, protocols, and instructions for the competition will be released soon. Please fill this form to get all the updates!