3D FACE MODELING

18 papers with code • 1 benchmarks • 5 datasets

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Most implemented papers

Learning a model of facial shape and expression from 4D scans

Rubikplayer/flame-fitting SIGGRAPH Asia 2017

FLAME is low-dimensional but more expressive than the FaceWarehouse model and the Basel Face Model.

Towards Fast, Accurate and Stable 3D Dense Face Alignment

cleardusk/3DDFA_V2 ECCV 2020

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.

Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

choyingw/SynergyNet 19 Oct 2021

Our synergy process leverages a representation cycle for 3DMM parameters and 3D landmarks.

DeepFace: Closing the Gap to Human-Level Performance in Face Verification

serengil/deepface Conference on Computer Vision and Pattern Recognition (CVPR) 2014

In modern face recognition, the conventional pipeline consists of four stages: detect => align => represent => classify.

Generating 3D faces using Convolutional Mesh Autoencoders

anuragranj/coma ECCV 2018

To address this, we introduce a versatile model that learns a non-linear representation of a face using spectral convolutions on a mesh surface.

Multilinear Wavelets: A Statistical Shape Space for Human Faces

TimoBolkart/MultilinearWaveletModel 13 Jan 2014

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

TimoBolkart/GlobalLocalFaceModels 4 Apr 2014

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

TimoBolkart/MultilinearModelFitting 24 Jun 2014

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

TimoBolkart/MultilinearMDL ICCV 2015

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.

A Robust Multilinear Model Learning Framework for 3D Faces

TimoBolkart/RobustMultilinearModel CVPR 2016

Multilinear models are widely used to represent the statistical variations of 3D human faces as they decouple shape changes due to identity and expression.