DualStyleGAN
encoder4editing
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| DualStyleGAN | encoder4editing | |
|---|---|---|
| 3 | 2 | |
| 1,557 | 912 | |
| - | - | |
| 0.7 | 0.0 | |
| about 1 year ago | 10 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 or later | MIT License |
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DualStyleGAN
- DualStyleGAN: A High-Resolution Portrait Style Transfer
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[R][P] Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer + Hugging Face Gradio Web Demo
Github: https://github.com/williamyang1991/DualStyleGAN
- "Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer", Yang et al 2022
encoder4editing
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[R] a Metric for finding the best StyleGAN Latent Encoders
Right now we have encoders like pSp and restyle or encoder4editing, but how can we tell which one performs better than the other?
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Edit a human face image with text-to-image using Google Colab notebook StyleCLIP by orpatashnik. 3 transformations shown. Details in a comment.
If you want to edit an existing image, the GitHub page says to use encoder4editing, but it currently has no code. If that is remedied, then set experiment_type=edit and latent_path to the output file generated by encoder4editing. If you use experiment_type=edit and latent_path=None, a random StyleGAN image is used.
What are some alternatives?
Cartoon-StyleGAN - Fine-tuning StyleGAN2 for Cartoon Face Generation
StyleCLIP - Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)
StyleCLIPDraw - Styled text-to-drawing synthesis method. Featured at IJCAI 2022 and the 2021 NeurIPS Workshop on Machine Learning for Creativity and Design
pixel2style2pixel - Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework
cartoonify - Deploy and scale serverless machine learning app - in 4 steps.
restyle-encoder - Official Implementation for "ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement" (ICCV 2021) https://arxiv.org/abs/2104.02699
TargetCLIP - [ECCV 2022] Official PyTorch implementation of the paper Image-Based CLIP-Guided Essence Transfer.
FixNoise - Official Pytorch Implementation for "Fix the Noise: Disentangling Source Feature for Controllable Domain Translation" (CVPR 2023, CVPRW 2022 Best paper)
PTI - Official Implementation for "Pivotal Tuning for Latent-based editing of Real Images" (ACM TOG 2022) https://arxiv.org/abs/2106.05744
Did-Somebody-Say-Corgi - Image Synthesis + Corgis = <3
GAN-Anime-Characters - Applied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.