Face Reconstruction
74 papers with code • 0 benchmarks • 3 datasets
Face reconstruction is the task of recovering the facial geometry of a face from an image.
( Image credit: Microsoft Deep3DFaceReconstruction )
Benchmarks
These leaderboards are used to track progress in Face Reconstruction
Most implemented papers
RetinaFace: Single-Shot Multi-Level Face Localisation in the Wild
Though tremendous strides have been made in uncontrolled face detection, accurate and efficient 2D face alignment and 3D face reconstruction in-the-wild remain an open challenge.
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
The 3D shapes of faces are well known to be discriminative.
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment.
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
Recently, deep learning based 3D face reconstruction methods have shown promising results in both quality and efficiency. However, training deep neural networks typically requires a large volume of data, whereas face images with ground-truth 3D face shapes are scarce.
Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression
Even though 3D face reconstruction has achieved impressive progress, most orthogonal projection-based face reconstruction methods can not achieve accurate and consistent reconstruction results when the face is very close to the camera due to the distortion under the perspective projection.
Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs
The relatively dense mesh model of 468 vertices is well-suited for face-based AR effects.
Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks
In this paper, we introduce a method to reconstruct 3D facial shapes with high-fidelity textures from single-view images in-the-wild, without the need to capture a large-scale face texture database.
Towards Fast, Accurate and Stable 3D Dense Face Alignment
Firstly, on the basis of a lightweight backbone, we propose a meta-joint optimization strategy to dynamically regress a small set of 3DMM parameters, which greatly enhances speed and accuracy simultaneously.
Face Alignment in Full Pose Range: A 3D Total Solution
In this paper, we propose to tackle these three challenges in an new alignment framework termed 3D Dense Face Alignment (3DDFA), in which a dense 3D Morphable Model (3DMM) is fitted to the image via Cascaded Convolutional Neural Networks.
3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild
3D face reconstruction from a single 2D image is a challenging problem with broad applications.