Search Results for author:
Found 2 papers, 2 papers with code
Perception-Oriented Single Image Super-Resolution using Optimal Objective Estimation
Specifically, the framework comprises two models: a predictive model that infers an optimal objective map for a given low-resolution (LR) input and a generative model that applies a target objective map to produce the corresponding SR output.
Ranked #1 on
Image Super-Resolution
on DIV2K val - 4x upscaling
Flexible Style Image Super-Resolution using Conditional Objective
Instead of using multiple models, we present a more efficient method to train a single adjustable SR model on various combinations of losses by taking advantage of multi-task learning.
Ranked #1 on
Image Super-Resolution
on General100 - 8x upscaling
