stylegan-encoder
AvatarGAN
stylegan-encoder | AvatarGAN | |
---|---|---|
1 | 1 | |
732 | 62 | |
- | - | |
0.0 | 3.8 | |
over 1 year ago | 7 months ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU General Public License v3.0 or later | - |
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.
stylegan-encoder
-
Someone help me find finetuned_resnet.h5 for StyleGAN encoder
Hi, I'm looking for a trained ResNet "finetuned_resnet.h5" for the styleGAN encoder(https://github.com/pbaylies/stylegan-encoder).
AvatarGAN
-
What will you do with your MtgoxNFT?
Could start with a GAN produced cartoon collection. https://github.com/aakashjhawar/AvatarGAN
What are some alternatives?
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
Deep-Learning - In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).
GAN-Anime-Characters - Applied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.
RefinementGAN - Official implementation of the paper: https://arxiv.org/abs/2108.04957
Transformer-in-Transformer - An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
faceswap-GAN - A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
pillbox - Contains implementation of AdVIL, AdRIL, and DAeQuIL algorithms from the ICML '21 Paper Of Moments and Matching.