205 citations · 759 across the 46 of their papers we have counts for
14 papers · 1 filter
Towards Personalization of User Preferences in Partially Observable Smart Home Environments
Shashi Suman, Francois Rivest, Ali Etemad
The technologies used in smart homes have recently improved to learn the user preferences from feedback in order to enhance the user convenience and quality of experience. Most sma…
Multi-View Video-Based 3D Hand Pose Estimation
Leyla Khaleghi, Alireza Sepas Moghaddam, Joshua Marshall +1
Hand pose estimation (HPE) can be used for a variety of human-computer interaction applications such as gesture-based control for physical or virtual/augmented reality devices. Rec…
Holistic Semi-Supervised Approaches for EEG Representation Learning
Guangyi Zhang, Ali Etemad
Recently, supervised methods, which often require substantial amounts of class labels, have achieved promising results for EEG representation learning. However, labeling EEG data i…
Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition
Guangyi Zhang, Ali Etemad
EEG-based emotion recognition often requires sufficient labeled training samples to build an effective computational model. Labeling EEG data, on the other hand, is often expensive…
Multi-Perspective LSTM for Joint Visual Representation Learning
Alireza Sepas-Moghaddam, Fernando Pereira, Paulo Lobato Correia +1
We present a novel LSTM cell architecture capable of learning both intra- and inter-perspective relationships available in visual sequences captured from multiple perspectives. Our…
Distilling EEG Representations via Capsules for Affective Computing
Guangyi Zhang, Ali Etemad
Affective computing with Electroencephalogram (EEG) is a challenging task that requires cumbersome models to effectively learn the information contained in large-scale EEG signals,…
Oriented Bounding Boxes for Small and Freely Rotated Objects
Mohsen Zand, Ali Etemad, Michael Greenspan
A novel object detection method is presented that handles freely rotated objects of arbitrary sizes, including tiny objects as small as pixels. Such tiny objects appear…
Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics
Mohsen Zand, Ali Etemad, Michael Greenspan
Conditional Normalizing Flows (CNFs) are flexible generative models capable of representing complicated distributions with high dimensionality and large interdimensional correlatio…
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting
Yangzheng Wu, Mohsen Zand, Ali Etemad +1
We propose a novel keypoint voting scheme based on intersecting spheres, that is more accurate than existing schemes and allows for fewer, more disperse keypoints. The scheme is ba…
Teacher-Student Adversarial Depth Hallucination to Improve Face Recognition
Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan +1
We present the Teacher-Student Generative Adversarial Network (TS-GAN) to generate depth images from single RGB images in order to boost the performance of face recognition systems…
Potential Impacts of Smart Homes on Human Behavior: A Reinforcement Learning Approach
Shashi Suman, Ali Etemad, Francois Rivest
We aim to investigate the potential impacts of smart homes on human behavior. To this end, we simulate a series of human models capable of performing various activities inside a re…
Deep Gait Recognition: A Survey
Alireza Sepas-Moghaddam, Ali Etemad
Gait recognition is an appealing biometric modality which aims to identify individuals based on the way they walk. Deep learning has reshaped the research landscape in this area si…
CapsField: Light Field-based Face and Expression Recognition in the Wild using Capsule Routing
Alireza Sepas-Moghaddam, Ali Etemad, Fernando Pereira +1
Light field (LF) cameras provide rich spatio-angular visual representations by sensing the visual scene from multiple perspectives and have recently emerged as a promising technolo…
Depth as Attention for Face Representation Learning
Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan +1
Face representation learning solutions have recently achieved great success for various applications such as verification and identification. However, face recognition approaches t…