DeepAI AI Chat
Log In Sign Up

BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs

03/11/2022
by   Araceli Morales, et al.
0

We present a 3D face reconstruction system that aims at recovering the 3D facial geometry of babies from uncalibrated photographs, BabyNet. Since the 3D facial geometry of babies differs substantially from that of adults, baby-specific facial reconstruction systems are needed. BabyNet consists of two stages: 1) a 3D graph convolutional autoencoder learns a latent space of the baby 3D facial shape; and 2) a 2D encoder that maps photographs to the 3D latent space based on representative features extracted using transfer learning. In this way, using the pre-trained 3D decoder, we can recover a 3D face from 2D images. We evaluate BabyNet and show that 1) methods based on adult datasets cannot model the 3D facial geometry of babies, which proves the need for a baby-specific method, and 2) BabyNet outperforms classical model-fitting methods even when a baby-specific 3D morphable model, such as BabyFM, is used.

READ FULL TEXT

page 10

page 19

page 21

page 24

page 25

11/05/2020

Transforming Facial Weight of Real Images by Editing Latent Space of StyleGAN

We present an invert-and-edit framework to automatically transform facia...
11/27/2019

Recovering Facial Reflectance and Geometry from Multi-view Images

While the problem of estimating shapes and diffuse reflectances of human...
08/23/2020

Geometry-guided Dense Perspective Network for Speech-Driven Facial Animation

Realistic speech-driven 3D facial animation is a challenging problem due...
03/25/2023

3D Facial Imperfection Regeneration: Deep learning approach and 3D printing prototypes

This study explores the potential of a fully convolutional mesh autoenco...
11/11/2020

Survey on 3D face reconstruction from uncalibrated images

Recently, a lot of attention has been focused on the incorporation of 3D...
07/19/2021

Synthesizing Human Faces using Latent Space Factorization and Local Weights (Extended Version)

We propose a 3D face generative model with local weights to increase the...