Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision

Example code for the FLAME 3D head model. The code demonstrates how to sample 3D heads from the model, fit the model to 3D keypoints and 3D scans.

This is a implementation of the 3D FLAME model in PyTorch

Photometric optimization code for creating the FLAME texture space and other applications

Tensorflow framework for the FLAME 3D head model. The code demonstrates how to sample 3D heads from the model, fit the model to 2D or 3D keypoints, and how to generate textured head meshes from Images.

Summary of publicly available ressources such as code, datasets, and scientific papers for the FLAME 3D head model

Convert from Basel Face Model (BFM) to the FLAME head model

Official Pytorch Implementation of SPECTRE: Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos

Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.

TEMPEH reconstructs 3D heads in dense semantic correspondence from calibrated multi-view images in about 0.3 seconds.

This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.

Blender Add-on for the FLAME face model

Mapping the Quantum Way across Prime Identity