StyleGAN_PyTorch VS stylegan3-editing

Compare StyleGAN_PyTorch vs stylegan3-editing and see what are their differences.

stylegan3-editing

Official Implementation of "Third Time's the Charm? Image and Video Editing with StyleGAN3" (AIM ECCVW 2022) https://arxiv.org/abs/2201.13433 (by yuval-alaluf)
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StyleGAN_PyTorch stylegan3-editing
- 2
533 637
- -
3.6 0.0
almost 4 years ago over 1 year ago
Python Python
- MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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StyleGAN_PyTorch

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

We haven't tracked posts mentioning StyleGAN_PyTorch yet.
Tracking mentions began in Dec 2020.

stylegan3-editing

Posts with mentions or reviews of stylegan3-editing. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing StyleGAN_PyTorch and stylegan3-editing you can also consider the following projects:

StyleFlow - StyleFlow: Attribute-conditioned Exploration of StyleGAN-generated Images using Conditional Continuous Normalizing Flows (ACM TOG 2021)

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

restyle-encoder - Official Implementation for "ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement" (ICCV 2021) https://arxiv.org/abs/2104.02699

ALAE - [CVPR2020] Adversarial Latent Autoencoders

checkface - Putting a face to a hash

PyTorch-StudioGAN - StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

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

GANce - Maps music and video into the latent space of StyleGAN networks.

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