Face Alignment
99 papers with code • 26 benchmarks • 17 datasets
Face alignment is the task of identifying the geometric structure of faces in digital images, and attempting to obtain a canonical alignment of the face based on translation, scale, and rotation.
( Image credit: 3DDFA_V2 )
Benchmarks
These leaderboards are used to track progress in Face Alignment
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Libraries
Use these libraries to find Face Alignment models and implementations
CelebA
300W
Helen
AFW
AFLW
LFPW
AFLW2000-3D
COFW
WFLW
FaceScape
Most implemented papers
Face Alignment in Full Pose Range: A 3D Total Solution
cleardusk/3DDFA
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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.
Look at Boundary: A Boundary-Aware Face Alignment Algorithm
By utilising boundary information of 300-W dataset, our method achieves 3. 92% mean error with 0. 39% failure rate on COFW dataset, and 1. 25% mean error on AFLW-Full dataset.
Generating 3D faces using Convolutional Mesh Autoencoders
To address this, we introduce a versatile model that learns a non-linear representation of a face using spectral convolutions on a mesh surface.
3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild
XgTu/2DASL-CNN
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3D face reconstruction from a single 2D image is a challenging problem with broad applications.
B-Spline CNNs on Lie Groups
ebekkers/gsplinets
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ICLR 2020
The impact and potential of our approach is studied on two benchmark datasets: cancer detection in histopathology slides in which rotation equivariance plays a key role and facial landmark localization in which scale equivariance is important.
Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild
The proposed model is equipped with a novel detection head based on heatmap regression, which conducts score and offset predictions simultaneously on low-resolution feature maps.
Structured Landmark Detection via Topology-Adapting Deep Graph Learning
Weijian-li/unsupervised_inter_intra_landmark
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ECCV 2020
Image landmark detection aims to automatically identify the locations of predefined fiducial points.
Heatmap Regression via Randomized Rounding
baoshengyu/H3R
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Previous methods to overcome the sub-pixel localization problem usually rely on high-resolution heatmaps.
Learning an Animatable Detailed 3D Face Model from In-The-Wild Images
YadiraF/DECA
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Some methods produce faces that cannot be realistically animated because they do not model how wrinkles vary with expression.
Pre-training strategies and datasets for facial representation learning
1adrianb/unsupervised-face-representation
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Recent work on Deep Learning in the area of face analysis has focused on supervised learning for specific tasks of interest (e. g. face recognition, facial landmark localization etc.)
