Ad examplesA 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.
All About The GanAll About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
ExposureLearning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.
Cartoongan TensorflowGenerate your own cartoon-style images with CartoonGAN (CVPR 2018), powered by TensorFlow 2.0 Alpha.
Pix2pixhdSynthesizing and manipulating 2048x1024 images with conditional GANs
Awesome GansAwesome Generative Adversarial Networks with tensorflow
Tensorflow Vae Gan DrawA collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).
GanomalyGANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
Tf TutorialsA collection of deep learning tutorials using Tensorflow and Python
Bmsg Gan[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation
HidtOfficial repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)
ApdrawingganCode for APDrawingGAN: Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs (CVPR 2019 Oral)
SeqganA simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)
Text To ImageGenerative Adversarial Text to Image Synthesis / Please Star -->
Ssgan TensorflowA Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).
Deep Learning Book《Deep Learning》《深度学习》 by Ian Goodfellow, Yoshua Bengio and Aaron Courville
T2fT2F: text to face generation using Deep Learning
Deblur GanKeras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
Textgan PytorchTextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.
RganRecurrent (conditional) generative adversarial networks for generating real-valued time series data.
Biggan PytorchPytorch implementation of LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS (BigGAN)
Tf.gans ComparisonImplementations of (theoretical) generative adversarial networks and comparison without cherry-picking
Cool Fashion Papers👔👗🕶️🎩 Cool resources about Fashion + AI! (papers, datasets, workshops, companies, ...) (constantly updating)
GanttsPyTorch implementation of GAN-based text-to-speech synthesis and voice conversion (VC)
Mimicry[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
MelganMelGAN vocoder (compatible with NVIDIA/tacotron2)
Generative ModelsAnnotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Enlightengan[IEEE TIP'2021] "EnlightenGAN: Deep Light Enhancement without Paired Supervision" by Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang
Generative CompressionTensorFlow Implementation of Generative Adversarial Networks for Extreme Learned Image Compression
Pro gan pytorchProGAN package implemented as an extension of PyTorch nn.Module
SimganImplementation of Apple's Learning from Simulated and Unsupervised Images through Adversarial Training
Pytorch RlThis repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
IganInteractive Image Generation via Generative Adversarial Networks
SeanSEAN: Image Synthesis with Semantic Region-Adaptive Normalization (CVPR 2020, Oral)
Autogan[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang
Gan TimelineA timeline showing the development of Generative Adversarial Networks (GAN).
MixupImplementation of the mixup training method
Anycost Gan[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
MsganMSGAN: Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis (CVPR2019)
Pytorch Mnist Celeba Gan DcganPytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets
SdvSynthetic Data Generation for tabular, relational and time series data.
PycadlPython package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"
Time Series PredictionA collection of time series prediction methods: rnn, seq2seq, cnn, wavenet, transformer, unet, n-beats, gan, kalman-filter
T81 558 deep learningWashington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
BasicocrBasicOCR是一个致力于解决自然场景文字识别算法研究的项目。该项目由长城数字大数据应用技术研究院佟派AI团队发起和维护。
Gan PlaygroundGAN Playground - Experiment with Generative Adversarial Nets in your browser. An introduction to GANs.