About

Face reconstruction is the task of recovering the facial geometry of a face from an image.

( Image credit: Microsoft Deep3DFaceReconstruction )

Benchmarks

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Subtasks

Datasets

Greatest papers with code

Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression

ICCV 2017 AaronJackson/vrn

Our CNN works with just a single 2D facial image, does not require accurate alignment nor establishes dense correspondence between images, works for arbitrary facial poses and expressions, and can be used to reconstruct the whole 3D facial geometry (including the non-visible parts of the face) bypassing the construction (during training) and fitting (during testing) of a 3D Morphable Model.

3D FACE RECONSTRUCTION FACE ALIGNMENT

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

ECCV 2018 YadiraF/PRNet

We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment.

3D FACE RECONSTRUCTION FACE ALIGNMENT FACE MODEL

Towards Fast, Accurate and Stable 3D Dense Face Alignment

ECCV 2020 cleardusk/3DDFA

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.

3D FACE MODELING 3D FACE RECONSTRUCTION FACE ALIGNMENT FACE RECOGNITION

Face Alignment in Full Pose Range: A 3D Total Solution

2 Apr 2018cleardusk/3DDFA

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 POSE ESTIMATION DEPTH IMAGE ESTIMATION FACE ALIGNMENT FACE MODEL FACE RECONSTRUCTION

Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set

20 Mar 2019Microsoft/Deep3DFaceReconstruction

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.

3D FACE RECONSTRUCTION

Extreme 3D Face Reconstruction: Seeing Through Occlusions

CVPR 2018 anhttran/extreme_3d_faces

Motivated by the concept of bump mapping, we propose a layered approach which decouples estimation of a global shape from its mid-level details (e. g., wrinkles).

3D FACE RECONSTRUCTION

AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"

CVPR 2020 lattas/avatarme

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.

3D FACE RECONSTRUCTION FACE GENERATION

GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction

CVPR 2019 barisgecer/ganfit

In this paper, we take a radically different approach and harness the power of Generative Adversarial Networks (GANs) and DCNNs in order to reconstruct the facial texture and shape from single images.

 Ranked #1 on 3D Face Reconstruction on Florence (Average 3D Error metric)

3D FACE RECONSTRUCTION