Heterogeneous Face Recognition

5 papers with code • 3 benchmarks • 2 datasets

Heterogeneous face recognition is the task of matching face images acquired from different sources (i.e., different sensors or different wavelengths) for identification or verification.

( Image credit: Pose Agnostic Cross-spectral Hallucination via Disentangling Independent Factors )

Most implemented papers

Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles

bob/bob.paper.tifs2022_hfr_prepended_domain_transformer 12 Oct 2022

The core idea of the proposed approach is to add a novel neural network block called Prepended Domain Transformer (PDT) in front of a pre-trained face recognition (FR) model to address the domain gap.

Dual Variational Generation for Low-Shot Heterogeneous Face Recognition

BradyFU/DVG 25 Mar 2019

Then, in order to ensure the identity consistency of the generated paired heterogeneous images, we impose a distribution alignment in the latent space and a pairwise identity preserving in the image space.

DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition

BradyFU/DVG 20 Sep 2020

As a consequence, massive new diverse paired heterogeneous images with the same identity can be generated from noises.