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The Wayback Machine - https://web.archive.org/web/20200602024552/https://github.com/topics/celeba
Here are
72 public repositories
matching this topic...
[CVPR2020] Adversarial Latent Autoencoders
Updated
May 2, 2020
Python
A large-scale face dataset for face parsing, recognition, generation and editing.
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May 20, 2020
Python
Implementations of (theoretical) generative adversarial networks and comparison without cherry-picking
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Mar 9, 2018
Python
Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"
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Jan 28, 2020
Python
Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets
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Jan 2, 2019
Python
Pytorch implementation of β-VAE
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Nov 28, 2018
Python
Experiments for understanding disentanglement in VAE latent representations
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Nov 29, 2019
Python
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset
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Aug 22, 2017
Python
Simple Implementation of many GAN models with PyTorch.
Updated
Nov 22, 2019
Jupyter Notebook
PyTorch Implementation of InfoGAN
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Jan 23, 2019
Python
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Jun 28, 2018
Python
MSG-GAN: Multi-Scale Gradients GAN (Architecture inspired from ProGAN but doesn't use layer-wise growing)
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Apr 12, 2020
Python
Tensorflow implementation of different GANs and their comparisions
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Nov 13, 2017
Python
To Obtain high resolution face images from CelebA
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Jan 3, 2020
Python
Updated
Dec 8, 2019
Jupyter Notebook
Modified h5tool.py make user getting celeba-HQ easier
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May 21, 2019
Python
use yolo v2 to train face detection model on CelebA dataset
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Nov 18, 2017
Python
Repository for implementation of generative models with Tensorflow 1.x
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May 10, 2020
Jupyter Notebook
PyTorch implementation of DCGAN
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Aug 21, 2017
Python
Who is your doppelgänger and more with Keras face recognition
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May 20, 2019
Jupyter Notebook
Download CelebA-HQ dataset easily ! Create with docker or download from Google Drive.
Updated
Aug 22, 2019
Python
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May 5, 2020
Python
Learning to Avoid Errors in GANs by Input Space Manipulation (Code for paper)
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Jul 7, 2017
Python
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Mar 5, 2019
Jupyter Notebook
PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)
Updated
Aug 28, 2017
Python
A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"
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Nov 24, 2017
Python
Study Friendly Implementation of DCGAN in Tensorflow
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Sep 8, 2018
Python
Implementation of BEGAN in Pytorch and other interpolation experiments
Updated
Dec 25, 2017
Python
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I started training with Celeb database, but around 50k iteration, the loss goes to NaN & k_t goes to 1. Have you seen this before.
10%|█████▎ | 49650/500000 [5:29:56<49:13:32, 2.54it/s][49650/500000] Loss_D: 0.112764 Loss_G: 0.053848 measure: 0.1190, k_t: 0.0458
10%|█████▎ | 49700/500000 [5:30:16<49:18