31 citations · 31 across the 2 of their papers we have counts for
8 papers
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…
View-Invariant Gait Recognition with Attentive Recurrent Learning of Partial Representations
Alireza Sepas-Moghaddam, Ali Etemad
Gait recognition refers to the identification of individuals based on features acquired from their body movement during walking. Despite the recent advances in gait recognition wit…
Gait Recognition using Multi-Scale Partial Representation Transformation with Capsules
Alireza Sepas-Moghaddam, Saeed Ghorbani, Nikolaus F. Troje +1
Gait recognition, referring to the identification of individuals based on the manner in which they walk, can be very challenging due to the variations in the viewpoint of the camer…
Two-Level Attention-based Fusion Learning for RGB-D Face Recognition
Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan +1
With recent advances in RGB-D sensing technologies as well as improvements in machine learning and fusion techniques, RGB-D facial recognition has become an active area of research…
Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network
Guangyi Zhang, Vandad Davoodnia, Alireza Sepas-Moghaddam +2
Classifying limb movements using brain activity is an important task in Brain-computer Interfaces (BCI) that has been successfully used in multiple application domains, ranging fro…
Face Recognition: A Novel Multi-Level Taxonomy based Survey
Alireza Sepas-Moghaddam, Fernando Pereira, Paulo Lobato Correia
In a world where security issues have been gaining growing importance, face recognition systems have attracted increasing attention in multiple application areas, ranging from fore…