Official Pytorch Implementation of SMIRK: 3D Facial Expressions through Analysis-by-Neural-Synthesis (CVPR 2024)
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Updated
May 31, 2024 - Python
Official Pytorch Implementation of SMIRK: 3D Facial Expressions through Analysis-by-Neural-Synthesis (CVPR 2024)
SeIF: Semantic-constrained Deep Implicit Function for Single-image 3D Head Reconstruction
Project page for our paper "REALY: Rethinking the Evaluation of 3D Face Reconstruction".
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
Sandbox for training deep learning networks
Upgrade your Android app with MiniAiLive's 3D Passive Face Liveness Detection! With our advanced computer vision techniques, you can now enhance security and accuracy on your Android platform. Check out our latest repository containing a demonstration of 2D & 3D passive face liveness detection capabilities. Try it out today!
[Siggraph '23] NeRSemble: Neural Radiance Field Reconstruction of Human Heads
Papers, Datasets, Benchmarks for 3D Face (Reconstruction, Talking head, etc)
使用ONNXRuntime部署3D人脸重建,人脸Mesh,人头姿势估计,包含C++和Python两个版本的程序
A lightweight 3D Morphable Face Model library in modern C++
A 3DMM fitting framework using Pytorch.
3DGANTex: 3D Face Reconstruction with StyleGAN3-based Texture Synthesis from Multi-View Images
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set (CVPRW 2019)
dense face landmark detection
🐳 Docker files for Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression
A high-fidelity 3D face reconstruction library from monocular RGB image(s)
CVPR 2023 - FitMe: Deep Photorealistic 3D Morphable Model Avatars
Public repository for the CVPR 2020 paper AvatarMe and the TPAMI 2021 AvatarMe++
[CVPR'23] Learning Neural Parametric Head Models
TEMPEH reconstructs 3D heads in dense semantic correspondence from calibrated multi-view images in about 0.3 seconds.
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