restyle-encoder
encoder4editing
restyle-encoder | encoder4editing | |
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2 | 2 | |
1,021 | 915 | |
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0.0 | 0.0 | |
over 1 year ago | 10 months ago | |
Python | Jupyter Notebook | |
MIT License | MIT License |
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restyle-encoder
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amazing april 7th
Found relevant code at https://yuval-alaluf.github.io/restyle-encoder/ + all code implementations here
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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?
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?
pixel2style2pixel - Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework
StyleCLIP - Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)
StyleGAN_PyTorch - The implementation of StyleGAN on PyTorch 1.0.1
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
DualStyleGAN - [CVPR 2022] Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer
SAM - Official Implementation for "Only a Matter of Style: Age Transformation Using a Style-Based Regression Model" (SIGGRAPH 2021) https://arxiv.org/abs/2102.02754
FixNoise - Official Pytorch Implementation for "Fix the Noise: Disentangling Source Feature for Controllable Domain Translation" (CVPR 2023, CVPRW 2022 Best paper)
SteganoGAN - SteganoGAN is a tool for creating steganographic images using adversarial training.
PTI - Official Implementation for "Pivotal Tuning for Latent-based editing of Real Images" (ACM TOG 2022) https://arxiv.org/abs/2106.05744
StyleFlow - StyleFlow: Attribute-conditioned Exploration of StyleGAN-generated Images using Conditional Continuous Normalizing Flows (ACM TOG 2021)
GAN-Anime-Characters - Applied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.