This codebase demonstrates how to synthesize realistic 3D character animations given an arbitrary speech signal and a static character mesh.

The idea of this list is to collect shared data and algorithms around 3D Morphable Models. You are invited to contribute to this list by adding a pull request. The original list arised from the Dagstuhl seminar on 3D Morphable Models https://www.dagstuhl.de/19102 in March 2019.

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.

Official repository accompanying a CVPR 2022 paper EMOCA: Emotion Driven Monocular Face Capture And Animation. EMOCA takes a single image of a face as input and produces a 3D reconstruction. EMOCA sets the new standard on reconstructing highly emotional images in-the-wild

A high-fidelity 3D face reconstruction library from monocular RGB image(s)

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

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

[CVPR'23] Learning Neural Parametric Head Models

Official Pytorch Implementation of SMIRK: 3D Facial Expressions through Analysis-by-Neural-Synthesis (CVPR 2024)

[CVPR 2024 Highlight]

Blender add-on to implement VOCA neural network.

Blender Add-on for the FLAME face model

Project Page of Synthesizing Normalized Faces From Facial Identity Features - [CVPR 2017]

The provided program loads a multilinear face model and fits this model to a point cloud or a triangle mesh.

Basel morphable face model mesh and texture generator using GPU.

The provided program loads a multilinear wavelet model and fits this model to a point cloud or a triangle mesh.

Fixed version of https://github.com/tomguluson92/PRNet_PyTorch

Flexible Object Reconstruction from Multiple Silhouettes. Cashman & Fitzgibbon, 'What Shape are Dolphins? Building 3D Morphable Models from 2D Images', 2012. Updated 2018, Jason Manley.