23 citations · 39 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
MGBPv2: Scaling Up Multi-Grid Back-Projection Networks
Pablo Navarrete Michelini, Wenbin Chen, Hanwen Liu +1
Here, we describe our solution for the AIM-2019 Extreme Super-Resolution Challenge, where we won the 1st place in terms of perceptual quality (MOS) similar to the ground truth and…
Multi-Scale Recursive and Perception-Distortion Controllable Image Super-Resolution
Pablo Navarrete Michelini, Dan Zhu, Hanwen Liu
We describe our solution for the PIRM Super-Resolution Challenge 2018 where we achieved the 2nd best perceptual quality for average RMSE<=16, 5th best for RMSE<=12.5, and 7th best…
Multigrid Backprojection Super-Resolution and Deep Filter Visualization
Pablo Navarrete Michelini, Hanwen Liu, Dan Zhu
We introduce a novel deep-learning architecture for image upscaling by large factors (e.g. 4x, 8x) based on examples of pristine high-resolution images. Our target is to reconstruc…