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GameUpV2-TSCUNet

2xTSCUNetby Kim2091

Purpose: Compression Removal, General Upscaler, Restoration

This is my first video model! It's aimed at restoring compressed video game footage, like what you'd get from Twitch or Youtube. I've attached an example below.

It's trained on TSCUNet using lossless game recordings, and degraded with my video destroyer. The degradations include resizing, and H264, H265, and AV1 compression.

IMPORTANT: You cannot use this model with chaiNNer or any other tool. You need to use this. You just run test_vsr.py after installing the requirements. Use the example command from the readme. You can also use the ONNX version of the model with test_onnx.py

If you want to train a TSCUNet model yourself, use traiNNer-redux. I've included scripts in the SCUNet repository to convert your own models to ONNX if desired.

Showcase: Watch in a Chrome based browser: https://video.yellowmouse.workers.dev/?key=Fvxw482Nsv8=

Animation

Training details (5)
Date
2025-03-28
Dataset
Custom game dataset
Dataset size
11150
Training iterations
160000
Training batch size
8

Downloads

Model

Architecture
TSCUNet
Scale
2x
Color Mode

Rights

CC-BY-NC-SA-4.0
Private use
Distribution
Modifications
Credit required
Same License
State Changes
No Liability & Warranty
Disclaimer

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