Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
-
Updated
Mar 24, 2023 - Python
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
A 3DMM fitting framework using Pytorch.
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.
FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset (CVPR2022)
[ECCV 2020] Reimplementation of 3DDFAv2, including face mesh, head pose, landmarks, and more.
[CVPR2023] A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images.
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
Official Pytorch Implementation of SPECTRE: Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos
The training and evaluation code for PRNet (《Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network》)
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.
Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation (ECCV2022)
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.
Facial Depth and Normal Estimation using Dual-Pixel Camera (ECCV 22)
Geometry-aware Face Reconstruction
Face API with Docker, Tensorflow, Keras and PyTorch.
[ICCVW 2023] TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces. 1st place at VSCHH @ ICCV 2023.
The implementation of this paper, in pytorch.
code used on the paper Face Reconstruction with Variational Autoencoder and Face Masks https://arxiv.org/abs/2112.02139
Add a description, image, and links to the face-reconstruction topic page so that developers can more easily learn about it.
To associate your repository with the face-reconstruction topic, visit your repo's landing page and select "manage topics."