3D Face Reconstruction
76 papers with code • 7 benchmarks • 11 datasets
3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
( Image credit: 3DDFA_V2 )
Libraries
Use these libraries to find 3D Face Reconstruction models and implementationsDatasets
Most implemented papers
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
It has been recently shown that neural networks can recover the geometric structure of a face from a single given image.
Unsupervised Training for 3D Morphable Model Regression
We train a regression network using these objectives, a set of unlabeled photographs, and the morphable model itself, and demonstrate state-of-the-art results.
3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild
3D face reconstruction from a single 2D image is a challenging problem with broad applications.
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
The estimation of 3D face shape from a single image must be robust to variations in lighting, head pose, expression, facial hair, makeup, and occlusions.
Learning an Animatable Detailed 3D Face Model from In-The-Wild Images
Some methods produce faces that cannot be realistically animated because they do not model how wrinkles vary with expression.
Pre-training strategies and datasets for facial representation learning
Recent work on Deep Learning in the area of face analysis has focused on supervised learning for specific tasks of interest (e. g. face recognition, facial landmark localization etc.)
HairMapper: Removing Hair From Portraits Using GANs
Removing hair from portrait images is challenging due to the complex occlusions between hair and face, as well as the lack of paired portrait data with/without hair.
FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
The ability to create high-quality 3D faces from a single image has become increasingly important with wide applications in video conferencing, AR/VR, and advanced video editing in movie industries.
Multilinear Wavelets: A Statistical Shape Space for Human Faces
We show that in comparison to a global multilinear model, our model better preserves fine detail and is computationally faster, while in comparison to a localized PCA model, our model better handles variation in expression, is faster, and allows us to fix identity parameters for a given subject.
A Multiresolution 3D Morphable Face Model and Fitting Framework
In this paper, we present the Surrey Face Model, a multi-resolution 3D Morphable Model that we make available to the public for non-commercial purposes.