398 Open source projects that are alternatives of or similar to Tf Sndcgan

Text to image synthesis using thought vectors

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DCGAN image generator 🖼️.

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

Implementation of some different variants of GANs by tensorflow, Train the GAN in Google Cloud Colab, DCGAN, WGAN, WGAN-GP, LSGAN, SNGAN, RSGAN, RaSGAN, BEGAN, ACGAN, PGGAN, pix2pix, BigGAN

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Software that can autocomplete sketches as the user starts drawing.

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🎎 InfoGAN: Interpretable Representation Learning

ArtGAN: This work presents a series of new approaches to improve Generative Adversarial Network (GAN) for conditional image synthesis and we name the proposed model as “ArtGAN”. Implementations are in Caffe/Tensorflow.

Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)

Tensorflow Implementation of Wasserstein GAN (and Improved version in wgan_v2)

Learning kernels to maximize the power of MMD tests

Grayscale Image Colorization with Generative Adversarial Networks. https://arxiv.org/abs/1803.05400

TF implementation of our ECCV 2018 paper: Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

FineGAN: Unsupervised Hierarchical Disentanglement for Fine-grained Object Generation and Discovery

Generative adversarial training for generating synthetic tabular data.

See Triple-GAN-V2 in PyTorch: https://github.com/taufikxu/Triple-GAN

EdgeConnect: Structure Guided Image Inpainting using Edge Prediction, ICCV 2019 https://arxiv.org/abs/1901.00212

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The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Tensorflow implementation for Conditional Convolutional Adversarial Networks.

Tensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.

The Implementation of paper "Controllable Person Image Synthesis with Attribute-Decomposed GAN"

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A stable algorithm for GAN training