Collection of generative models in Pytorch version.
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Updated
Apr 12, 2020 - Python
Collection of generative models in Pytorch version.
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset
My implementation of various GAN (generative adversarial networks) architectures like vanilla GAN (Goodfellow et al.), cGAN (Mirza et al.), DCGAN (Radford et al.), etc.
Simple Implementation of many GAN models with PyTorch.
Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Tensorflow implementation for Conditional Convolutional Adversarial Networks.
[NeurIPS 2022] Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models
Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.
In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).
Pytorch implementation of pix2pix for various datasets.
Generative Adversarial Networks in TensorFlow 2.0
Text to Image Synthesis using Generative Adversarial Networks
The implementation of 'Image synthesis via semantic composition', ICCV2021.
[MICCAI'21] [Tensorflow] Retinal Vessel Segmentation using a Novel Multi-scale Generative Adversarial Network
PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)
Conditional Sequence Generative Adversarial Network trained with policy gradient, Implementation in Tensorflow
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