FixNoise
gan-vae-pretrained-pytorch
| FixNoise | gan-vae-pretrained-pytorch | |
|---|---|---|
| 2 | 1 | |
| 179 | 170 | |
| - | - | |
| 3.9 | 0.0 | |
| 12 months ago | over 2 years 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.
FixNoise
-
[R] Fix the Noise: Disentangling Source Feature for Transfer Learning of StyleGAN (CVPRW 2022)
Paper: https://arxiv.org/abs/2204.14079
-
[R]Fix the Noise: Disentangling Source Feature for Transfer Learning of StyleGAN
Github: https://github.com/LeeDongYeun/FixNoise
gan-vae-pretrained-pytorch
-
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?
pixel2style2pixel - Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework
AvatarGAN - Generate Cartoon Images using Generative Adversarial Network
encoder4editing - Official implementation of "Designing an Encoder for StyleGAN Image Manipulation" (SIGGRAPH 2021) https://arxiv.org/abs/2102.02766
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!
PixelAlchemist - Semantic image editing in realtime with a multi-parameter interface for StyleCLIP global directions
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
DualStyleGAN - [CVPR 2022] Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
stylegan2-projecting-images - Projecting images to latent space with StyleGAN2.
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.
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
JoJoGAN - Official PyTorch repo for JoJoGAN: One Shot Face Stylization