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 implementationsMost implemented papers
Deep Neural Networks Regularization for Structured Output Prediction
The motivation of this work is to learn the output dependencies that may lie in the output data in order to improve the prediction accuracy.
A Multiresolution 3D Morphable Face Model and Fitting Framework
In this paper, we present the Surrey Face Model, a multi-resolution 3D Morphable Model that we make available to the public for non-commercial purposes.
Convolutional Experts Constrained Local Model for Facial Landmark Detection
In our work, we present a novel local detector -- Convolutional Experts Network (CEN) -- that brings together the advantages of neural architectures and mixtures of experts in an end-to-end framework.
Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detection
This Estimation-Correction-Tuning process perfectly combines the advantages of the global robustness of data-driven method (FCN), outlier correction capability of model-driven method (PDM) and non-parametric optimization of RLMS.
A Deep Regression Architecture With Two-Stage Re-Initialization for High Performance Facial Landmark Detection
At the global stage, given an image with a rough face detection result, the full face region is firstly re-initialized by a supervised spatial transformer network to a canonical shape state and then trained to regress a coarse landmark estimation.
Dockerface: an Easy to Install and Use Faster R-CNN Face Detector in a Docker Container
Face detection is a very important task and a necessary pre-processing step for many applications such as facial landmark detection, pose estimation, sentiment analysis and face recognition.
Dense Face Alignment
Face alignment is a classic problem in the computer vision field.
Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection
We show that CNNs connected with our Deep Collaboration obtain better accuracy on facial landmark detection with related tasks.
ExpNet: Landmark-Free, Deep, 3D Facial Expressions
Our ExpNet CNN is applied directly to the intensities of a face image and regresses a 29D vector of 3D expression coefficients.
Style Aggregated Network for Facial Landmark Detection
In this work, we propose a style-aggregated approach to deal with the large intrinsic variance of image styles for facial landmark detection.