VRT VS JoJoGAN

Compare VRT vs JoJoGAN and see what are their differences.

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VRT JoJoGAN
1 11
1,244 1,400
- -
0.0 0.0
10 months ago over 1 year ago
Python Jupyter Notebook
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

VRT

Posts with mentions or reviews of VRT. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-26.

JoJoGAN

Posts with mentions or reviews of JoJoGAN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-26.

What are some alternatives?

When comparing VRT and JoJoGAN you can also consider the following projects:

articulated-animation - Code for Motion Representations for Articulated Animation paper

AnimeGANv3 - Use AnimeGANv3 to make your own animation works, including turning photos or videos into anime.

InstColorization

ArcaneGAN - ArcaneGAN

RethinkVSRAlignment - (NIPS 2022) Rethinking Alignment in Video Super-Resolution Transformers

gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

maxim-pytorch - [CVPR 2022 Oral] PyTorch re-implementation for "MAXIM: Multi-Axis MLP for Image Processing", with *training code*. Official Jax repo: https://github.com/google-research/maxim

toonify

AnimeGANv2 - [Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

pixel2style2pixel - Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework