SBS11 RRDB

Category: Pretrained SOFVSR Models
Purpose: Anime - interpolation

Sample video: https://cdn.discordapp.com/attachments/724353640521007145/873861876352704533/1.webm

cainliteanime

Category: Pretrained SOFVSR Models
Purpose: Anime - interpolation

cvpv6

Category: Pretrained SOFVSR Models
Purpose: Animethemes

I think one of sharpest models for anime. Sample video: https://cdn.discordapp.com/attachments/579685650824036387/1002663424695750686/output.mp4

Plz don't steal without credits, k thx.

explodV1

Category: Pretrained SOFVSR Models
Purpose: Video Frame Interpolation for anime openings
Pretrained: My ~~first~~ (ok technically second) attempt to create a video frame interpolation model and I like how it turned out. To use it, you can either use https://gitlab.com/hubert.sontowski2007/cainapp, https://github.com/styler00dollar/Colab-CAIN or the bot in [Game Upscale] (model called rvpv1 there, just use --model rvpv1). Some demo videos in pcloud, but you need to download them. The web player seems to playback in low fps. The architecture is mainly the same to the original CAIN, but i modified the padding to be zero padding instead. ``.pt`` means JIT model, `.pth`, means normal pytorch model. Architecture file is in pcloud as well. And no, no cupscale or flowframes.

Sample video: https://files.catbox.moe/xiq9vi.mp4

rvpV1

Category: Pretrained SOFVSR Models
Purpose: Animation interpolation

I never really mentioned it in model-releases prior since I think not too many care about interpolation here, but I trained a rife4 model for animation a some months ago, which is better than rife4 and rife4.2 imo. Thought I should also mention it here as well. I also converted it into ncnn. (Nihuis rife ncnn models are only exported with the fastest mode and not the best quality. I exported ncnn models for the most important quality settings. Due to different export/quality settings, there are multiple models. For that reason alone, my ncnn models are much better too, since nihui only exported the fastest one.) My https://github.com/styler00dollar/VSGAN-tensorrt-docker also has the rife ncnn extention, which can use VMAF, dedup, scene detection and so on, which I would recommend. My models are in that extention as well, just select model 10, 11 or 12 and use the dev docker. That test video is done with 2x framerate, enbemble True and FastMode False, combined with scene detection and dedup stuff, tta False. Towards the best quality rife can do. Plz don't steal without credits, k thx.

Pretrained model: RifeV4

Sample video: https://cdn.discordapp.com/attachments/579685650824036387/990345004260151296/ngnl_sudorife.mp4

sudo rife4 testV1 scale1

Category: Pretrained Discriminators


none

Video TSSM

Video TSSM RRDB

Category: Pretrained Discriminators
Purpose: IRL videos

upscale IRL videos. Use not recommended by creator.

Sample video: https://cdn.discordapp.com/attachments/547949806761410560/813134983236419664/100k_iter.mp4

SOFVSR_REDS_F3 V1

Category: Pretrained SOFVSR Models
Purpose: 

Trained on REDS' size dataset

Architecture	SOFVSR
Scale	2x
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	2020-12-03
Dataset	Every 6 frames from every episode of Spongebob Season 11 (DVD and HD). DVD was resized with Spline36 to 540p. LR also got extra OTF JPEG (1/4 chance) and sharpening (15% chance)
Dataset size	126956
Training iterations	111000
Training epochs	11
Training batch size	6
Training HR size	128

SBS11 RRDB

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