Name: 4x KCJPUNK
Author: KCJPUNK

AbeScale

Interpolation between 4x-UltraSharp and 4x-TextSharp-v0.5. Works amazingly on anime. It also upscales text, but it's far better with anime content. I rebranded this model on 2/10/22 to 4x-AnimeSharp from 4x-TextSharpV1.

Pretrained model: Interpolation between 4x-UltraSharp and 4x-TextSharp-v0.5

AnimeSharp

Comic / Drawings. Trained on Custom (Spider-Man) dataset

Comic Book

Purpose: Digital Animation

Replica of DigitalFrames 2.1 but interpolatable

DigitalFake 2.1

Purpose: upscale anime from dvd

Anime upscale from dvd with x4, a little softer lines and look but keeps the colors.

https://imgsli.com/MjM3ODEy

Drawimation compact

Falcon Fanart

Fatal_Anime

FatalimiX

Purpose: 4x anime upscaler handling video compression artifacts, trained for 200 epochs

4x anime upscaler handling video compression artifacts since trained with otf degradations for "mpeg2video", "libxvid", "libx264", "libx265" with crf 20-32, mpeg bitrate 3800-5800 (together with the standard Real-ESRGAN otf pipeline). A faster arch using this otf degradation pipeline would be great for handling video compression artifacts. Since this one is a GRL model and therefore slow, [as noted by the dev](https://github.com/Kiteretsu77/VCISR-official/issues/3) maybe more for research purposes (or more for single images/screenshots). Trained using [VCISR](https://github.com/Kiteretsu77/VCISR-official) for 200 epochs.  

"This is epoch 200 and the start iteration is 85959 with learning rate 2.5e-05"  

Slow Pics examples:  
[h264_crf28](https://slow.pics/c/fqOnxXep)  
[ludvae1](https://slow.pics/c/OcukRy7d)  
[ludvae2](https://slow.pics/c/FI33mX4F)

HFA2k VCISR GRLGAN ep200

Purpose: Digital Animation

Up-scaling Digital Animation

KCJPUNK

Pretrained model: 4x_DIV2K-Lite_1M (`4x_NMKD-YandereNeo-Lite_320k` for the 2x conversion)

NMKD YandereNeo (4x)

NMKD YandereNeo Superlite

NMKD YandereNeo XL

This model was made for my project captain tsubasa anime so i don't know if it works good for anything else. just try it ;)

OLDIES_ALTERNATIVE_FINAL

i made this model to upscale old anime and denoise.

OLDIES_FINAL

Purpose: Anime/Pretrained

NTSC DVD-spec encode x4 scale super-resolution for Anime Drawing style content. The dataset has a LOT of data throughout almost every frame, so it had a lot of stuff to learn. The resulting DVD-spec encode also had some blocking at times so it also learned to fight off blocking.

Sol Levante NTSC2HD

SpongeBob

Restorative CEL Animation MPEG-1 and 2 Model specifically crafted for SpongeBob S01.

SpongeBob.CEL.2.HD.125ki.499e-PHOENiX

New version of the Spongebob model. Ideally it's a lot sharper and cleaner but I'm still not sure if it works better than the old one. From what I can tell it's better in many cases.

Spongebob v6

Purpose: Animation - Quantized

A model I trained to do both de-quantizing as well as upscaling. The results are pretty blurry but it works decently for what it is.

Spongebob v6 De-Quantize

This model is based on a private model by @eula 5600x 3070 named 4x_eula_anifilm_v1_225k. He sent me a copy of the model, and I decided to train a compact model based on it with his permission. This model seems to fix the majority of the issues the original model had while being far faster, it's just a tiny bit softer in some images.

The dataset consists of Dragon Ball movies converted to YUV24 with @sgdisk --zap-all /dev/sda's help to reduce artifacts, then upscaled with ArtClarity and eula_anifilm. LRs are the original frames right from DVD. As a result, this model corrects some color space issues. The 2x model's HRs were downscaled by 50% with Lanczos.

The 2x and 4x models are pretty close in output despite being trained separately. The 2x model is a bit softer overall.

The models in the Real-ESRGAN Compatible folder are the original output from Real-ESRGANs training code for compatibility reasons.

Anifilm Compact (4x)

Anime super-resolution, with real degradation.

animerd v1

This is the first community model using the OmniSR network. I trained it mostly to test this network.\nNote: the model output decreases brightness. This is a well known issue we had with OmniSR.

4x_ardo

Purpose: Anime / Visual Novel Art

Third iteration of my eroge upscaling model. Discriminator: https://drive.google.com/file/d/18q-4ktFNZ8tPjkszuoG6kVBhCjKl8iFa/view?usp=sharing

escale

Upscaling cel animation. Trained this more than a year ago, releasing cause I've got a much better v2 and v3 now.

Architecture	ESRGAN
Scale	4x
Size	64nf23nb
Color Mode	RGB
License	CC-BY-NC-SA-4.0 Private use Distribution Modifications Credit required Same License State Changes No Liability & Warranty Disclaimer
Date	2021-03-23
Dataset	1080P BD anime frames
Dataset size	20000
Training iterations	233089
Training epochs	274
Training batch size	4
Training HR size	128
Training OTF	No

KCJPUNK

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