496 Open source projects that are alternatives of or similar to Improvedgan Pytorch

Code for paper "Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation"

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace

An implementation for our paper: CsiGAN: Robust Channel State Information-based Activity Recognition with GANs (IEEE Internet of Things Journal, 2019), which is the semi-supervised Generative Adversarial Network (GAN) for Channel State Information (CSI) -based activity recognition.

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

Pytorch implementation of Conditional Image Synthesis with Auxiliary Classifier GANs

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

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.

PyTorch implementation of Adversarially Learned Inference (BiGAN).

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

Tensorflow implementation for Conditional Convolutional Adversarial Networks.

VOSK Speech Recognition Toolkit

Tensorflow implementation of generative adversarial imitation learning

Text to image synthesis using thought vectors

DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral

Observations and notes to understand the workings of neural network models and other thought experiments using Tensorflow

DCGAN image generator 🖼️.

[ICCV 2019]Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Transition

A collection of arbitrary text to image papers with code (constantly updating)

GANnotation (PyTorch): Landmark-guided face to face synthesis using GANs (And a triple consistency loss!)

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

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

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.

Deep learning codes and projects using Python

MMD-GAN: Towards Deeper Understanding of Moment Matching Network

Code for "On the Effects of Batch and Weight Normalization in Generative Adversarial Networks"

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

Learning kernels to maximize the power of MMD tests

ICCV 2019 (oral) RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution. PyTorch implementation

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

Coherent Semantic Attention for image inpainting(ICCV 2019)

Generative adversarial training for generating synthetic tabular data.

This is the official PyTorch implementation of the CVPR 2020 paper "TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting".

[CVPR 2020] Semi-Supervised Semantic Segmentation with Cross-Consistency Training.

Autoencoders for Link Prediction and Semi-Supervised Node Classification (DSAA 2018)

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

Cross-domain Correspondence Learning for Exemplar-based Image Translation. (CVPR 2020 Oral)

Pytorch deep learning face frontalization model

Auxiliary Classifier Generative Adversarial Networks in Keras

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

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

A DCGAN to generate anime faces using custom mined dataset

Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs (CVPRW 2020)

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution

(WIP) Implementation of Creative Adversarial Networks https://arxiv.org/pdf/1706.07068.pdf

Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement

OpenMMLab Image and Video Editing Toolbox

Collection of generative models in Pytorch version.

Unsupervised anomaly detection with generative model, keras implementation

Generative Adversarial Networks and Autoencoders for 3D Shapes

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

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

A stable algorithm for GAN training

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

Tensorflow implementation of PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION

A curated collection of adversarial attack and defense on graph data.

Implementation of the paper "NetGAN: Generating Graphs via Random Walks".

Software that can autocomplete sketches as the user starts drawing.