Code repo for "Implicit Transformer Network for Screen ContentImage Continuous Super-Resolution" (NeurIPS'21)

codyshen0000, updated 🕥 2022-04-05 05:41:57

ITSRN

Code repo for "Implicit Transformer Network for Screen Content Image Continuous Super-Resolution"

Issues

Can you provide the test configuration

opened on 2023-01-01 16:54:56 by Meow-2

test.py requires a configuration file in a specific format to run

SCI1K-compression JPEG compression quality factor

opened on 2022-04-04 05:22:07 by Byeong-Hyun

Hi, I have a question about SCI1K-compression dataset.

Your paper stated that the quality factor of JPEG compression is randomly selected from 75, 85, and 95.

However, in wrappers.py and image_folder_compress.py, the code for quality factor is commented out as "qf = random.randrange(10, 75)".

I think that to follow the statement in paper, "qf = random.randrange(75, 96, 10)" is right code.

What code did you use for training and testing on SCI1K-compression?