Decomposing multispectral face images into diffuse and specular shading and biophysical parameters

02/18/2019
by   Sarah Alotaibi, et al.
0

We propose a novel biophysical and dichromatic reflectance model that efficiently characterises spectral skin reflectance. We show how to fit the model to multispectral face images enabling high quality estimation of diffuse and specular shading as well as biophysical parameter maps (melanin and haemoglobin). Our method works from a single image without requiring complex controlled lighting setups yet provides quantitatively accurate reconstructions and qualitatively convincing decomposition and editing.

READ FULL TEXT

page 3

page 4

research
09/06/2017

Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images

Lighting estimation from face images is an important task and has applic...
research
11/25/2022

FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction

We present a large-scale facial UV-texture dataset that contains over 50...
research
08/28/2018

On Learning 3D Face Morphable Model from In-the-wild Images

As a classic statistical model of 3D facial shape and albedo, 3D Morphab...
research
03/15/2019

Smart, Deep Copy-Paste

In this work, we propose a novel system for smart copy-paste, enabling t...
research
08/16/2019

FSGAN: Subject Agnostic Face Swapping and Reenactment

We present Face Swapping GAN (FSGAN) for face swapping and reenactment. ...
research
02/25/2022

FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment

We present Face Swapping GAN (FSGAN) for face swapping and reenactment. ...
research
02/17/2021

Re-identification of Individuals in Genomic Datasets Using Public Face Images

DNA sequencing is becoming increasingly commonplace, both in medical and...

Please sign up or login with your details

Forgot password? Click here to reset