the-gan-zoo VS pytorch-CycleGAN-and-pix2pix

Compare the-gan-zoo vs pytorch-CycleGAN-and-pix2pix and see what are their differences.

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the-gan-zoo pytorch-CycleGAN-and-pix2pix
1 3
11,303 16,290
- -
0.0 5.9
3 months ago 4 days ago
Python Python
MIT License GNU General Public License v3.0 or later
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.

the-gan-zoo

Posts with mentions or reviews of the-gan-zoo. We have used some of these posts to build our list of alternatives and similar projects.

pytorch-CycleGAN-and-pix2pix

Posts with mentions or reviews of pytorch-CycleGAN-and-pix2pix. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing the-gan-zoo and pytorch-CycleGAN-and-pix2pix you can also consider the following projects:

pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs

PaddleGAN - PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, wav2lip, picture repair, image editing, photo2cartoon, image style transfer, and so on.

Anime-face-generation-DCGAN-webapp - A port of my Anime face generation using Pytorch into a Webapp

CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

anycost-gan - [CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

Im2Vec - [CVPR 2021 Oral] Im2Vec Synthesizing Vector Graphics without Vector Supervision

DeepSIM - Official PyTorch implementation of the paper: "DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample" (ICCV 2021 Oral)

Deep-Fakes