23 citations · 30 across the 7 of their papers we have counts for
12 papers
edge-SR: Super-Resolution For The Masses
Pablo Navarrete Michelini, Yunhua Lu, Xingqun Jiang
Classic image scaling (e.g. bicubic) can be seen as one convolutional layer and a single upscaling filter. Its implementation is ubiquitous in all display devices and image process…
Back-Projection Pipeline
Pablo Navarrete Michelini, Hanwen Liu, Yunhua Lu +1
We propose a simple extension of residual networks that works simultaneously in multiple resolutions. Our network design is inspired by the iterative back-projection algorithm but…
Multi-Grid Back-Projection Networks
Pablo Navarrete Michelini, Wenbin Chen, Hanwen Liu +2
Multi-Grid Back-Projection (MGBP) is a fully-convolutional network architecture that can learn to restore images and videos with upscaling artifacts. Using the same strategy of mul…
AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results
Dario Fuoli, Zhiwu Huang, Shuhang Gu +23
This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR)…
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte +87
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new versi…
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +43
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world settin…