research
∙
10/05/2021
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation
In medical image segmentation, supervised deep networks' success comes a...
share
research
∙
04/06/2021
Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images
Existing reference (RF)-based super-resolution (SR) models try to improv...
research
∙
07/06/2020
Benefitting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution
Super-resolution (SR) has traditionally been based on pairs of high-reso...
research
∙
08/20/2019
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution
By benefiting from perceptual losses, recent studies have improved signi...
research
∙
07/29/2019
Benefiting from Multitask Learning to Improve Single Image Super-Resolution
Despite significant progress toward super resolving more realistic image...
research
∙
05/17/2019
Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis
Cross-domain synthesizing realistic faces to learn deep models has attra...
research
∙
05/01/2019
Learn to synthesize and synthesize to learn
Attribute guided face image synthesis aims to manipulate attributes on a...
research
∙
10/31/2017
