3D Face Reconstruction
76 papers with code • 7 benchmarks • 11 datasets
3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
( Image credit: 3DDFA_V2 )
Benchmarks
These leaderboards are used to track progress in 3D Face Reconstruction
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Libraries
Use these libraries to find 3D Face Reconstruction models and implementationsDatasets
AFLW2000-3D
FaceWarehouse
FaceScape
Florence
ExPose
NoW Benchmark
REALY
FFHQ-UV
DAD-3DHeads
FaMoS
Latest papers
3D Face Reconstruction Using A Spectral-Based Graph Convolution Encoder
To overcome this limitation and enhance the reconstruction of 3D structural features, we propose an innovative approach that integrates existing 2D features with 3D features to guide the model learning process.
Eye Motion Matters for 3D Face Reconstruction
Recent advances in single-image 3D face reconstruction have shown remarkable progress in various applications.
3D Face Reconstruction with the Geometric Guidance of Facial Part Segmentation
In this paper, we fully utilize the facial part segmentation geometry by introducing Part Re-projection Distance Loss (PRDL).
Instant Multi-View Head Capture through Learnable Registration
TimoBolkart/TEMPEH
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CVPR 2023
We use raw MVS scans as supervision during training, but, once trained, TEMPEH directly predicts 3D heads in dense correspondence without requiring scans.
FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
billyxyb/facednerf
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NeurIPS 2023
The ability to create high-quality 3D faces from a single image has become increasingly important with wide applications in video conferencing, AR/VR, and advanced video editing in movie industries.
DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment
Thanks to the proposed fusion module, our method is robust not only to occlusion and large pitch and roll view angles, which is the benefit of our image space approach, but also to noise and large yaw angles, which is the benefit of our model space method.
Towards Realistic Generative 3D Face Models
aashishrai3799/Towards-Realistic-Generative-3D-Face-Models
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By combining 2D face generative models with semantic face manipulation, this method enables editing of detailed 3D rendered faces.
Face Animation with an Attribute-Guided Diffusion Model
Face animation has achieved much progress in computer vision.
A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images
Meanwhile, 3D priors of facial details are incorporated to enhance the accuracy and authenticity of the reconstruction results.
RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs
We propose a robust and accurate non-parametric method for single-view 3D face reconstruction (SVFR).
