AvatarGAN
gan-vae-pretrained-pytorch
AvatarGAN | gan-vae-pretrained-pytorch | |
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1 | 1 | |
62 | 170 | |
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3.8 | 0.0 | |
7 months ago | over 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
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AvatarGAN
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What will you do with your MtgoxNFT?
Could start with a GAN produced cartoon collection. https://github.com/aakashjhawar/AvatarGAN
gan-vae-pretrained-pytorch
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DCGAN (CIFAR-10) Generating fake images is easy, but how to also output the class label (1 to 10) with the fake generated images?
I have this DCGAN model (https://github.com/csinva/gan-vae-pretrained-pytorch/tree/master/cifar10_dcgan) which generates fake Cifar-10 images. However I also want to get the intended class label output with the fake generated images. How can I do this? This model which I found only generates fake images but doesn't know what class the generated images belong to.
What are some alternatives?
Deep-Learning - In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).
pytorch-GAT - My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
GAN-Anime-Characters - Applied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
RefinementGAN - Official implementation of the paper: https://arxiv.org/abs/2108.04957
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
Transformer-in-Transformer - An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
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, ... 🧠
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
faceswap-GAN - A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
JoJoGAN - Official PyTorch repo for JoJoGAN: One Shot Face Stylization