Mopaint🎨💪 Modern, modular paint and more! (pre-alpha, not much done yet)
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Dcgan TensorflowA tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
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Vc With GanVoice Conversion with GANs
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MsganMSGAN: Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis (CVPR2019)
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Unified Gan TensorflowA Tensorflow implementation of GAN, WGAN and WGAN with gradient penalty.
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Tac GanA Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions (https://arxiv.org/abs/1703.06412)
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Transgan[Preprint] "TransGAN: Two Transformers Can Make One Strong GAN", Yifan Jiang, Shiyu Chang, Zhangyang Wang
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InterpretFit interpretable models. Explain blackbox machine learning.
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DaliDali is an image blur library for Android. It contains several modules for static blurring, live blurring and animations.
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Time Series PredictionA collection of time series prediction methods: rnn, seq2seq, cnn, wavenet, transformer, unet, n-beats, gan, kalman-filter
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SeganA PyTorch implementation of SEGAN based on INTERSPEECH 2017 paper "SEGAN: Speech Enhancement Generative Adversarial Network"
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MindseyeNeural Networks in Java 8 with CuDNN and Aparapi
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L1stabilizer🎥 Video stabilization using L1-norm optimal camera paths.
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CometaSuper fast, on-demand and on-the-fly, image processing.
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T81 558 deep learningWashington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
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Jsi GanOfficial repository of JSI-GAN (Accepted at AAAI 2020).
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ConganContinious Generative Adversarial Network
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O GanO-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks
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Neural DoodleTurn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)
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Inverse Style GanLooking up a generative latent vectors from (face) reference images.
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Deepfashion try onOfficial code for "Towards Photo-Realistic Virtual Try-On by Adaptively Generating↔Preserving Image Content",CVPR‘20 https://arxiv.org/abs/2003.05863
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Generate to adaptImplementation of "Generate To Adapt: Aligning Domains using Generative Adversarial Networks"
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Pytorch AddaA PyTorch implementation for Adversarial Discriminative Domain Adaptation
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3d conditional ganThe codes of VAE-GAN model for 3d shape reconstruction from depth data
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DmtDisentangled Makeup Transfer with Generative Adversarial Network
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CycleganPyTorch implementation of CycleGAN
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Watimage🖼 PHP image manipulation class
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Improved Video GanGitHub repository for "Improving Video Generation for Multi-functional Applications"
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ImageneA General Purpose Image Manipulation Tool
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Mnist inception scoreTraining a MNIST classifier, and use it to compute inception score (ICP)
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Cloudinary jsCloudinary JavaScript library
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CtganConditional GAN for generating synthetic tabular data.
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Deep Generative ModelsDeep 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)
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CanvacordPowerful image manipulation tool to manipulate images easily.
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Nag[CVPR 2018] Tensorflow implementation of NAG : Network for Adversary Generation
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AshpyTensorFlow 2.0 library for distributed training, evaluation, model selection, and fast prototyping.
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UnsupntsUnsupervised Neural Text Simplification
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Csmri RefinementCode for "Adversarial and Perceptual Refinement Compressed Sensing MRI Reconstruction"
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Generative Evaluation PrdcCode base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
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Unet Stylegan2A Pytorch implementation of Stylegan2 with UNet Discriminator
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Inr GanAdversarial Generation of Continuous Images [CVPR 2021]
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Began TensorflowTensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
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CadganICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.
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AliceNIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching
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