Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
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Updated
Mar 24, 2023 - Python
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
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
A 3DMM fitting framework using Pytorch.
FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset (CVPR2022)
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.
[CVPR2023] A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images.
[ECCV 2020] Reimplementation of 3DDFAv2, including face mesh, head pose, landmarks, and more.
Official Pytorch Implementation of SPECTRE: Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos
Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation (ECCV2022)
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
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.
The training and evaluation code for PRNet (《Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network》)
Facial Depth and Normal Estimation using Dual-Pixel Camera (ECCV 22)
2D face reconstruction using SFSNet, and end-to-end learning framework for producing an accurate decomposition of an unconstrained human face image into shape, reflectance and illuminance.
[ICCVW 2023] TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces. 1st place at VSCHH @ ICCV 2023.
code used on the paper Face Reconstruction with Variational Autoencoder and Face Masks https://arxiv.org/abs/2112.02139
Geometry-aware Face Reconstruction
Face API with Docker, Tensorflow, Keras and PyTorch.
Volumetric Regression Network based on the work of Aaron S. Jackson - Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression"
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