1986 Open source projects that are alternatives of or similar to Gpnd

A curated list of dedicated resources and applications

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

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

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

Invert the color of MNIST images with PyTorch

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

Focal Frequency Loss for Generative Models

Unsupervised anomaly detection with generative model, keras implementation

🎎 InfoGAN: Interpretable Representation Learning

Collection of generative models in Pytorch version.

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

PyTorch reimplementation of the paper: "Semantic Pyramid for Image Generation" [CVPR 2020].

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

Page to PAGE Layout Analysis Tool

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

The implementation of Relativistic average GAN with Keras

Synthesizing and manipulating 2048x1024 images with conditional GANs

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Generative Adversarial Networks and Autoencoders for 3D Shapes

[CVPR2020] Adversarial Latent Autoencoders

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

Official PyTorch implementation of NICE-GAN: Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

A Pytorch implementation for the ZeroSpeech 2019 challenge.

🔥🔥 PyTorch implementation of "Progressive growing of GANs (PGGAN)" 🔥🔥

Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

Speech Enhancement Generative Adversarial Network in TensorFlow

Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.

Next RecSys Library

An application tool of edge-connect, which can do anime inpainting and drawing. 动漫人物图片自动修复，去马赛克，填补，去瑕疵

🦋A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.

Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.

[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

InstaGAN: Instance-aware Image Translation (ICLR 2019)

An AI for Music Generation

tensorflow implementation of Exploring Randomly Wired Neural Networks for Image Recognition

Dataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"

🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating)

Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)

Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

Projecting images to latent space with StyleGAN2.

Generative Adversarial Networks in Keras

An implementation of CycleGan using TensorFlow

Generate your own cartoon-style images with CartoonGAN (CVPR 2018), powered by TensorFlow 2.0 Alpha.

Advanced Deep Learning with Keras, published by Packt

Deep generative models implemented with TensorFlow 2.0: eg. Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Deep Boltzmann Machine (DBM), Convolutional Variational Auto-Encoder (CVAE), Convolutional Generative Adversarial Network (CGAN)

Pytorch implementation of Conditional Image Synthesis with Auxiliary Classifier GANs

Tensorflow implementation of different GANs and their comparisions

Image-to-image translation with conditional adversarial nets

Using Machine Learning to predict the type of exercise from movement data

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

PyTorch implementation of Adversarially Learned Inference (BiGAN).

[NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks