AIMC Topic: Face

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Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning.

IEEE transactions on pattern analysis and machine intelligence
Face hallucination is a domain-specific super-resolution problem that aims to generate a high-resolution (HR) face image from a low-resolution (LR) input. In contrast to the existing patch-wise super-resolution models that divide a face image into re...

An algorithm for learning shape and appearance models without annotations.

Medical image analysis
This paper presents a framework for automatically learning shape and appearance models for medical (and certain other) images. The algorithm was developed with the aim of eventually enabling distributed privacy-preserving analysis of brain image data...

Geometric morphometrics aided by machine learning in craniofacial surgery.

Journal of orthodontics
Geometric morphometrics aided by machine learning provide detailed and accurate statistical models of facial form. They promise to be extremely effective tools in surgical planning and assessment; however, a clinical tool to use this information is s...

Detecting changes in facial temperature induced by a sudden auditory stimulus based on deep learning-assisted face tracking.

Scientific reports
Thermal Imaging (Infrared-Imaging-IRI) is a promising new technique for psychophysiological research and application. Unlike traditional physiological measures (like skin conductance and heart rate), it is uniquely contact-free, substantially enhanci...

Polymer Analog Memristive Synapse with Atomic-Scale Conductive Filament for Flexible Neuromorphic Computing System.

Nano letters
With the advent of artificial intelligence (AI), memristors have received significant interest as a synaptic building block for neuromorphic systems, where each synaptic memristor should operate in an analog fashion, exhibiting multilevel accessible ...

Face-from-Depth for Head Pose Estimation on Depth Images.

IEEE transactions on pattern analysis and machine intelligence
Depth cameras allow to set up reliable solutions for people monitoring and behavior understanding, especially when unstable or poor illumination conditions make unusable common RGB sensors. Therefore, we propose a complete framework for the estimatio...

Face Recognition Using the SR-CNN Model.

Sensors (Basel, Switzerland)
In order to solve the problem of face recognition in complex environments being vulnerable to illumination change, object rotation, occlusion, and so on, which leads to the imprecision of target position, a face recognition algorithm with multi-featu...

Deep CNNs with Robust LBP Guiding Pooling for Face Recognition.

Sensors (Basel, Switzerland)
Pooling layer in Convolutional Neural Networks (CNNs) is designed to reduce dimensions and computational complexity. Unfortunately, CNN is easily disturbed by noise in images when extracting features from input images. The traditional pooling layer d...

Intraspectrum Discrimination and Interspectrum Correlation Analysis Deep Network for Multispectral Face Recognition.

IEEE transactions on cybernetics
Multispectral images contain rich recognition information since the multispectral camera can reveal information that is not visible to the human eye or to the conventional RGB camera. Due to this characteristic of multispectral images, multispectral ...

High-Fidelity Monocular Face Reconstruction Based on an Unsupervised Model-Based Face Autoencoder.

IEEE transactions on pattern analysis and machine intelligence
In this work, we propose a novel model-based deep convolutional autoencoder that addresses the highly challenging problem of reconstructing a 3D human face from a single in-the-wild color image. To this end, we combine a convolutional encoder network...