AIMC Topic: Face

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EAC-Net: Deep Nets with Enhancing and Cropping for Facial Action Unit Detection.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we propose a deep learning based approach for facial action unit (AU) detection by enhancing and cropping regions of interest of face images. The approach is implemented by adding two novel nets (a.k.a. layers): the enhancing layers an...

Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

EBioMedicine
BACKGROUND: Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability.

HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition.

IEEE transactions on pattern analysis and machine intelligence
We present an algorithm for simultaneous face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNN). The proposed method called, HyperFace, fuses the intermediate layers of a deep CNN...

Efficient Group-n Encoding and Decoding for Facial Age Estimation.

IEEE transactions on pattern analysis and machine intelligence
Different ages are closely related especially among the adjacent ages because aging is a slow and extremely non-stationary process with much randomness. To explore the relationship between the real age and its adjacent ages, an age group-n encoding (...

Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video.

IEEE transactions on pattern analysis and machine intelligence
Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition. The success mainly derives from learning a discriminant Riemannian metric which encodes the non-linear geo...

A Simple, Fast and Highly-Accurate Algorithm to Recover 3D Shape from 2D Landmarks on a Single Image.

IEEE transactions on pattern analysis and machine intelligence
Three-dimensional shape reconstruction of 2D landmark points on a single image is a hallmark of human vision, but is a task that has been proven difficult for computer vision algorithms. We define a feed-forward deep neural network algorithm that can...

Deep Convolutional Neural Networks for Classifying Body Constitution Based on Face Image.

Computational and mathematical methods in medicine
Body constitution classification is the basis and core content of traditional Chinese medicine constitution research. It is to extract the relevant laws from the complex constitution phenomenon and finally build the constitution classification system...

Error-Correcting Factorization.

IEEE transactions on pattern analysis and machine intelligence
Error Correcting Output Codes (ECOC) is a successful technique in multi-class classification, which is a core problem in Pattern Recognition and Machine Learning. A major advantage of ECOC over other methods is that the multi-class problem is decoupl...

Multiple Cayley-Klein metric learning.

PloS one
As a specific kind of non-Euclidean metric lies in projective space, Cayley-Klein metric has been recently introduced in metric learning to deal with the complex data distributions in computer vision tasks. In this paper, we extend the original Cayle...

Sharable and Individual Multi-View Metric Learning.

IEEE transactions on pattern analysis and machine intelligence
This paper presents a sharable and individual multi-view metric learning (MvML) approach for visual recognition. Unlike conventional metric leaning methods which learn a distance metric on either a single type of feature representation or a concatena...