IDE-3D
[SIGGRAPH Asia 2022] IDE-3D: Interactive Disentangled Editing For High-Resolution 3D-aware Portrait Synthesis (by MrTornado24)
faceswap-GAN
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping. (by shaoanlu)
| IDE-3D | faceswap-GAN | |
|---|---|---|
| 2 | 1 | |
| 465 | 3,328 | |
| - | - | |
| 10.0 | 0.0 | |
| over 1 year ago | about 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | - |
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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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.
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.
IDE-3D
Posts with mentions or reviews of IDE-3D.
We have used some of these posts to build our list of alternatives
and similar projects.
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A Recent AI Research Proposes IDE-3D: An Interactive Disentangled Editing Framework for High-Resolution 3D-aware Portrait Synthesis
Quick Read: https://www.marktechpost.com/2023/02/07/a-recent-ai-research-proposes-ide-3d-an-interactive-disentangled-editing-framework-for-high-resolution-3d-aware-portrait-synthesis/ Paper: https://arxiv.org/pdf/2205.15517.pdf Github: https://github.com/MrTornado24/IDE-3D
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IDE-3D: Interactive Disentangled Editing for High-Resolution 3D-aware Portrait Synthesis
Code: https://github.com/MrTornado24/IDE-3D
faceswap-GAN
Posts with mentions or reviews of faceswap-GAN.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-28.
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[D] How is it checked if models do not just memorize their training examples?
But there's a nice survey on Arxiv here of various deepfake / face swap methods. Some of methods listed in the table on page 4, such as Faceswap and Faceswap-GAN, apparently use encoder-decoder models. I think Faceswap-GAN was the one that I was thinking of in particular; apparently it adds a perceptual loss and an adversarial loss to an autoencoder.
What are some alternatives?
When comparing IDE-3D and faceswap-GAN you can also consider the following projects:
nerf - Code release for NeRF (Neural Radiance Fields)
faceswap - Deepfakes Software For All
CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
AvatarGAN - Generate Cartoon Images using Generative Adversarial Network
DCT-Net - Official implementation of "DCT-Net: Domain-Calibrated Translation for Portrait Stylization", SIGGRAPH 2022 (TOG); Multi-style cartoonization
ydata-synthetic - Synthetic data generators for tabular and time-series data