80 citations · 80 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
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…