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Facial Landmark Detection

7 papers with code · Computer Vision

Facial landmark detection is the task of detecting key landmarks on the face and tracking them (being robust to rigid and non-rigid facial deformations due to head movements and facial expressions).

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Greatest papers with code

FacePoseNet: Making a Case for Landmark-Free Face Alignment

24 Aug 2017fengju514/Face-Pose-Net

We show how a simple convolutional neural network (CNN) can be trained to accurately and robustly regress 6 degrees of freedom (6DoF) 3D head pose, directly from image intensities. Instead, we compare our FPN with existing methods by evaluating how they affect face recognition accuracy on the IJB-A and IJB-B benchmarks: using the same recognition pipeline, but varying the face alignment method.

FACE ALIGNMENT FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION FACIAL LANDMARK DETECTION

Style Aggregated Network for Facial Landmark Detection

CVPR 2018 D-X-Y/SAN

In this work, we propose a style-aggregated approach to deal with the large intrinsic variance of image styles for facial landmark detection. Moreover, we show the robustness of our method to the large variance of image styles by comparing to a variant of our approach, in which the generative adversarial module is removed, and no style-aggregated images are used.

FACIAL LANDMARK DETECTION

ExpNet: Landmark-Free, Deep, 3D Facial Expressions

2 Feb 2018fengju514/Expression-Net

Our ExpNet CNN is applied directly to the intensities of a face image and regresses a 29D vector of 3D expression coefficients. We further offer a novel means of evaluating the accuracy of estimated expression coefficients: by measuring how well they capture facial emotions on the CK+ and EmotiW-17 emotion recognition benchmarks.

3D FACIAL EXPRESSION RECOGNITION EMOTION RECOGNITION FACIAL LANDMARK DETECTION

Dockerface: an Easy to Install and Use Faster R-CNN Face Detector in a Docker Container

15 Aug 2017natanielruiz/dockerface

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. Not only is face detection an important pre-processing step in computer vision applications but also in computational psychology, behavioral imaging and other fields where researchers might not be initiated in computer vision frameworks and state-of-the-art detection applications.

FACE DETECTION FACE RECOGNITION FACIAL LANDMARK DETECTION POSE ESTIMATION SENTIMENT ANALYSIS

Super-realtime facial landmark detection and shape fitting by deep regression of shape model parameters

9 Feb 2019justusschock/shapenet

We present a method for highly efficient landmark detection that combines deep convolutional neural networks with well established model-based fitting algorithms. Instead of computing the model parameters using iterative optimization, the PCA is included in a deep neural network using a novel layer type.

FACIAL LANDMARK DETECTION MEDICAL IMAGE SEGMENTATION SEMANTIC SEGMENTATION

Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection

ICLR 2018 ltrottier/deep-collaboration-network

Convolutional neural networks (CNNs) have become the most successful approach in many vision-related domains. We show that CNNs connected with our Deep Collaboration obtain better accuracy on facial landmark detection with related tasks.

FACIAL LANDMARK DETECTION MULTI-TASK LEARNING

Deep Neural Networks Regularization for Structured Output Prediction

28 Apr 2015sbelharbi/structured-output-ae

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. In order to overcome this issue, we propose in this paper a regularization scheme for training neural networks for these particular tasks using a multi-task framework.

FACIAL LANDMARK DETECTION