Python project on “Finding set of faces when combined results in face of person A". The application is deployed as PIP Library.
-
Updated
Dec 14, 2021 - Python
Python project on “Finding set of faces when combined results in face of person A". The application is deployed as PIP Library.
The implementation of this paper, in pytorch.
Reconstruct depth face image
Face Reconstructor: Mediapipe Holistic + OpenCV for accurate facial landmark detection and mesh-based skin patching
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"
Face API with Docker, Tensorflow, Keras and PyTorch.
Geometry-aware Face Reconstruction
code used on the paper Face Reconstruction with Variational Autoencoder and Face Masks https://arxiv.org/abs/2112.02139
[ICCVW 2023] TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces. 1st place at VSCHH @ ICCV 2023.
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)
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.
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation (ECCV2022)
Official Pytorch Implementation of SPECTRE: Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos
[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.
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.
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."