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
Most implemented papers
Face Manifold: Manifold Learning for Synthetic Face Generation
The main challenge of such techniques is a vital need for large 3D face datasets.
Self-supervised Learning of Detailed 3D Face Reconstruction
cyj907/unsupervised-detail-layer
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The displacement map and the coarse model are used to render a final detailed face, which again can be compared with the original input image to serve as a photometric loss for the second stage.
Cross-modal Deep Face Normals with Deactivable Skip Connections
boukhayma/face_normals
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CVPR 2020
Core to our approach is a novel module that we call deactivable skip connections, which allows integrating both the auto-encoded and image-to-normal branches within the same architecture that can be trained end-to-end.
Lightweight Photometric Stereo for Facial Details Recovery
Juyong/FacePSNet
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CVPR 2020
Recently, 3D face reconstruction from a single image has achieved great success with the help of deep learning and shape prior knowledge, but they often fail to produce accurate geometry details.
AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
Over the last years, with the advent of Generative Adversarial Networks (GANs), many face analysis tasks have accomplished astounding performance, with applications including, but not limited to, face generation and 3D face reconstruction from a single "in-the-wild" image.
Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model
To this end, we first build a dataset with various styles of 2D caricatures and their corresponding 3D shapes, and then build a parametric model on vertex based deformation space for 3D caricature face.
Deep Facial Non-Rigid Multi-View Stereo
zqbai-jeremy/dfnrmvs
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CVPR 2020
We facilitate it with a CNN network that learns to regularize the non-rigid 3D face according to the input image and preliminary optimization results.
Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency
jiaxiangshang/MGCNet
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ECCV 2020
Recent learning-based approaches, in which models are trained by single-view images have shown promising results for monocular 3D face reconstruction, but they suffer from the ill-posed face pose and depth ambiguity issue.
Monocular Expressive Body Regression through Body-Driven Attention
To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image.
Weakly-Supervised Multi-Face 3D Reconstruction
kalyo-zjl/WM3DR
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3D face reconstruction plays a very important role in many real-world multimedia applications, including digital entertainment, social media, affection analysis, and person identification.
