Heterogeneous Face Recognition

5 papers with code • 3 benchmarks • 1 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 )

Datasets


Most implemented papers

Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation

ZhaoJ9014/face.evoLVe.PyTorch 26 May 2019

Recent deep learning based face recognition methods have achieved great performance, but it still remains challenging to recognize very low-resolution query face like 28x28 pixels when CCTV camera is far from the captured subject.

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.