Facial Landmark Detection
47 papers with code • 9 benchmarks • 15 datasets
Facial Landmark Detection is a computer vision task that involves detecting and localizing specific points or landmarks on a face, such as the eyes, nose, mouth, and chin. The goal is to accurately identify these landmarks in images or videos of faces in real-time and use them for various applications, such as face recognition, facial expression analysis, and head pose estimation.
( Image credit: Style Aggregated Network for Facial Landmark Detection )
Libraries
Use these libraries to find Facial Landmark Detection models and implementationsLatest papers
img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation
Tests on AFLW2000-3D and BIWI show that our method runs at real-time and outperforms state of the art (SotA) face pose estimators.
Teacher-Student Asynchronous Learning with Multi-Source Consistency for Facial Landmark Detection
The radical student uses multi-source supervision signals from the same task to update parameters, while the calm teacher uses a single-source supervision signal to update parameters.
Robust Facial Landmark Detection by Multi-order Multi-constraint Deep Networks
Recently, heatmap regression has been widely explored in facial landmark detection and obtained remarkable performance.
Deep Structured Prediction for Facial Landmark Detection
Existing deep learning based facial landmark detection methods have achieved excellent performance.
Whole-Body Human Pose Estimation in the Wild
This paper investigates the task of 2D human whole-body pose estimation, which aims to localize dense landmarks on the entire human body including face, hands, body, and feet.
AnchorFace: An Anchor-based Facial Landmark Detector Across Large Poses
Based on the prediction of each anchor template, we propose to aggregate the results, which can reduce the landmark uncertainty due to the large poses.
A Detailed Look At CNN-based Approaches In Facial Landmark Detection
To the best of our knowledge, using the PWC model to detect facial landmarks have not been comprehensively studied.
LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood
In this paper, we present a novel framework for jointly predicting landmark locations, associated uncertainties of these predicted locations, and landmark visibilities.
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.
Learning to Impute: A General Framework for Semi-supervised Learning
Recent semi-supervised learning methods have shown to achieve comparable results to their supervised counterparts while using only a small portion of labels in image classification tasks thanks to their regularization strategies.