license: cc-by-4.0
pipeline_tag: image-to-image
tags:
- pytorch
- super-resolution
- pretrain
4xmssim_realplksr_dysample_pretrain
Scale: 4
Architecture: RealPLKSR with Dysample
Architecture Option: realplksr
Author: Philip Hofmann
License: CC-BY-0.4
Purpose: Pretrained
Subject: Photography
Input Type: Images
Release Date: 27.06.2024
Dataset: nomosv2
Dataset Size: 6000
OTF (on the fly augmentations): No
Pretrained Model: None (=From Scratch)
Iterations: 200'000
Batch Size: 8
GT Size: 192, 512
Description: Dysample had been recently added to RealPLKSR, which from what I had seen can resolve or help avoid the checkerboard / grid pattern on inference outputs. So with the commits from three days ago, the 24.06.24, on neosr, I wanted to create a 4x photo pretrain I can then use to train more realplksr models with dysample specifically to stabilize training at the beginning.