3D Face Modelling
21 papers with code • 2 benchmarks • 4 datasets
Most implemented papers
Learning a model of facial shape and expression from 4D scans
FLAME is low-dimensional but more expressive than the FaceWarehouse model and the Basel Face Model.
Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
Our synergy process leverages a representation cycle for 3DMM parameters and 3D landmarks.
Towards Fast, Accurate and Stable 3D Dense Face Alignment
Firstly, on the basis of a lightweight backbone, we propose a meta-joint optimization strategy to dynamically regress a small set of 3DMM parameters, which greatly enhances speed and accuracy simultaneously.
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
In modern face recognition, the conventional pipeline consists of four stages: detect => align => represent => classify.
Generating 3D faces using Convolutional Mesh Autoencoders
To address this, we introduce a versatile model that learns a non-linear representation of a face using spectral convolutions on a mesh surface.
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.
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.
Review of Statistical Shape Spaces for 3D Data with ComparativeAnalysis for Human Faces
Due to the wide avail-ability of databases of high-quality data, we use the human face as the specific shape we wish to extract from corrupted data.
3D faces in motion: Fully automatic registration and statistical analysis
The resulting statistical analysis is applied to automatically generate realistic facial animations and to recognize dynamic facial expressions.
A Groupwise Multilinear Correspondence Optimization for 3D Faces
To compute a high-quality multilinear face model, the quality of the registration of the database of 3D face scans used for training is essential.