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

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

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.

[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.

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

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

Regional 3D face reconstruction (Ocular Region)

From coin to 3D face sculpture of roman emperors