AIMC Journal:
IEEE transactions on pattern analysis and machine intelligence

Showing 231 to 240 of 300 articles

LCR-Net++: Multi-Person 2D and 3D Pose Detection in Natural Images.

IEEE transactions on pattern analysis and machine intelligence
We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images. Key to our approach is the generation and scoring of a number of pose proposals per image, which allows us to predict 2D and 3D poses of multiple peopl...

3D Human Pose Machines with Self-Supervised Learning.

IEEE transactions on pattern analysis and machine intelligence
Driven by recent computer vision and robotic applications, recovering 3D human poses has become increasingly important and attracted growing interests. In fact, completing this task is quite challenging due to the diverse appearances, viewpoints, occ...

Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI.

IEEE transactions on pattern analysis and machine intelligence
Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided diagnosis of neurodegenerative disorders, e.g., Alzheimer's disease (AD), due to its sensitivity to morphological changes caused by brain atrophy. Recently, a few de...

The Whole Is More Than Its Parts? From Explicit to Implicit Pose Normalization.

IEEE transactions on pattern analysis and machine intelligence
Fine-grained classification describes the automated recognition of visually similar object categories like birds species. Previous works were usually based on explicit pose normalization, i.e., the detection and description of object parts. However, ...

Unsupervised Person Re-Identification by Deep Asymmetric Metric Embedding.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (Re-ID) aims to match identities across non-overlapping camera views. Researchers have proposed many supervised Re-ID models which require quantities of cross-view pairwise labelled data. This limits their scalabilities to ma...

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...

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...

Discriminant Functional Learning of Color Features for the Recognition of Facial Action Units and Their Intensities.

IEEE transactions on pattern analysis and machine intelligence
Color is a fundamental image feature of facial expressions. For example, when we furrow our eyebrows in anger, blood rushes in, turning some face areas red; or when one goes white in fear as a result of the drainage of blood from the face. Surprising...

Representation Learning by Rotating Your Faces.

IEEE transactions on pattern analysis and machine intelligence
The large pose discrepancy between two face images is one of the fundamental challenges in automatic face recognition. Conventional approaches to pose-invariant face recognition either perform face frontalization on, or learn a pose-invariant represe...

Personalized Saliency and Its Prediction.

IEEE transactions on pattern analysis and machine intelligence
Nearly all existing visual saliency models by far have focused on predicting a universal saliency map across all observers. Yet psychology studies suggest that visual attention of different observers can vary significantly under specific circumstance...