AIMC Topic: Face

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Cross-Generation Kinship Verification with Sparse Discriminative Metric.

IEEE transactions on pattern analysis and machine intelligence
Kinship verification is a very important technique in many real-world applications, e.g., personal album organization, missing person investigation and forensic analysis. However, it is extremely difficult to verify a family pair with generation gap,...

3D-Aided Dual-Agent GANs for Unconstrained Face Recognition.

IEEE transactions on pattern analysis and machine intelligence
Synthesizing realistic profile faces is beneficial for more efficiently training deep pose-invariant models for large-scale unconstrained face recognition, by augmenting the number of samples with extreme poses and avoiding costly annotation work. Ho...

Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition.

IEEE transactions on pattern analysis and machine intelligence
Heterogeneous face recognition (HFR) aims at matching facial images acquired from different sensing modalities with mission-critical applications in forensics, security and commercial sectors. However, HFR presents more challenging issues than tradit...

An Integrated Neural Framework for Dynamic and Static Face Processing.

Scientific reports
Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face are...

Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

Australasian physical & engineering sciences in medicine
Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each...

Intuitive Assessment of Mortality Based on Facial Characteristics: Behavioral, Electrocortical, and Machine Learning Analyses.

Explore (New York, N.Y.)
Studies of various characteristics of the human face indicate that it contains a wealth of information about health status. Most studies involve objective measurement of facial features as correlated with historical health information. But some indiv...

Recurrent Shape Regression.

IEEE transactions on pattern analysis and machine intelligence
An end-to-end network architecture, the Recurrent Shape Regression (RSR), is presented to deal with the task of facial shape detection, a crucial step in many computer vision problems. The RSR generalizes the conventional cascaded regression into a r...

On the Reconstruction of Face Images from Deep Face Templates.

IEEE transactions on pattern analysis and machine intelligence
State-of-the-art face recognition systems are based on deep (convolutional) neural networks. Therefore, it is imperative to determine to what extent face templates derived from deep networks can be inverted to obtain the original face image. In this ...

Visual Kinship Recognition of Families in the Wild.

IEEE transactions on pattern analysis and machine intelligence
We present the largest database for visual kinship recognition, Families In the Wild (FIW), with over 13,000 family photos of 1,000 family trees with 4-to-38 members. It took only a small team to build FIW with efficient labeling tools and work-flow....

An Automatic Diagnosis Method of Facial Acne Vulgaris Based on Convolutional Neural Network.

Scientific reports
In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vul...