106 citations · 213 across the 42 of their papers we have counts for
8 papers · 1 filter
Revisiting Few-Shot Learning for Facial Expression Recognition
Anca-Nicoleta Ciubotaru, Arnout Devos, Behzad Bozorgtabar +2
Most of the existing deep neural nets on automatic facial expression recognition focus on a set of predefined emotion classes, where the amount of training data has the biggest imp…
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution
Mohammad Saeed Rad, Behzad Bozorgtabar, Urs-Viktor Marti +3
By benefiting from perceptual losses, recent studies have improved significantly the performance of the super-resolution task, where a high-resolution image is resolved from its lo…
Benefiting from Multitask Learning to Improve Single Image Super-Resolution
Mohammad Saeed Rad, Behzad Bozorgtabar, Claudiu Musat +4
Despite significant progress toward super resolving more realistic images by deeper convolutional neural networks (CNNs), reconstructing fine and natural textures still remains a c…
Exploring Factors for Improving Low Resolution Face Recognition
Omid Abdollahi Aghdam, Behzad Bozorgtabar, Hazım Kemal Ekenel +1
State-of-the-art deep face recognition approaches report near perfect performance on popular benchmarks, e.g., Labeled Faces in the Wild. However, their performance deteriorates si…
Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis
Behzad Bozorgtabar, Mohammad Saeed Rad, Hazim Kemal Ekenel +1
Cross-domain synthesizing realistic faces to learn deep models has attracted increasing attention for facial expression analysis as it helps to improve the performance of expressio…
Learn to synthesize and synthesize to learn
Behzad Bozorgtabar, Mohammad Saeed Rad, Hazım Kemal Ekenel +1
Attribute guided face image synthesis aims to manipulate attributes on a face image. Most existing methods for image-to-image translation can either perform a fixed translation bet…
Informative sample generation using class aware generative adversarial networks for classification of chest Xrays
Behzad Bozorgtabar, Dwarikanath Mahapatra, Hendrik von Teng +4
Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem…
Progressive Generative Adversarial Networks for Medical Image Super resolution
Dwarikanath Mahapatra, Behzad Bozorgtabar
Anatomical landmark segmentation and pathology localization are important steps in automated analysis of medical images. They are particularly challenging when the anatomy or patho…