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702 public repositories
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This repository contains the source code for the paper First Order Motion Model for Image Animation
Updated
Aug 24, 2022
Jupyter Notebook
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
Updated
Jan 6, 2021
JavaScript
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Updated
May 17, 2022
Python
Code for the paper "Jukebox: A Generative Model for Music"
Updated
Sep 10, 2021
Python
Collection of generative models in Tensorflow
Updated
Aug 8, 2022
Python
[CVPR2020] Adversarial Latent Autoencoders
Updated
Jan 23, 2021
Python
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
Updated
Aug 5, 2022
Python
A collection of resources and papers on Diffusion Models and Score-based Models, a darkhorse in the field of Generative Models
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Updated
Aug 22, 2022
Python
Research Framework for easy and efficient training of GANs based on Pytorch
Updated
Oct 19, 2021
Python
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
This repository contains the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"
Updated
Feb 9, 2022
Python
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
Updated
Mar 26, 2018
Jupyter Notebook
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
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Mar 26, 2018
Python
Unifying Generative Autoencoder implementations in Python
Updated
Aug 24, 2022
Python
Generative Adversarial Networks (GANs) resources sorted by citations
Speech Enhancement Generative Adversarial Network in TensorFlow
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Jun 21, 2022
Python
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
Updated
Apr 27, 2022
Python
The idea of this list is to collect shared data and algorithms around 3D Morphable Models. You are invited to contribute to this list by adding a pull request. The original list arised from the Dagstuhl seminar on 3D Morphable Models
https://www.dagstuhl.de/19102 in March 2019.
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