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Type: Organization
Type: Organization
Face Identity Disentanglement via Latent Space Mapping [SIGGRAPH ASIA 2020]
Official implementation of "Foreground-aware Semantic Representations for Image Harmonization"
PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
Diverse Image Outpainting via GAN Inversion
[NeurIPS 2021] Data-Efficient Instance Generation from Instance Discrimination
An Introduction to Deep Generative Modeling: Examples
Official Code for Invertible Residual Networks
iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs
Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2:
In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represent the inferred \textbf{latent data distribution}, i.e. its topology and structural properties. We propose LaDDer to achieve accurate modelling of the latent data distribution in a variational autoencoder framework and to facilitate better representation learning. The central idea of LaDDer is a meta-embedding concept, which uses multiple VAE models to learn an embedding of the embeddings, forming a ladder of encodings. We use a non-parametric mixture as the hyper prior for the innermost VAE and learn all the parameters in a unified variational framework. From extensive experiments, we show that our LaDDer model is able to accurately estimate complex latent distribution and results in improvement in the representation quality.
LaFIn: Generative Landmark Guided Face Inpainting
Pytorch implementation of LCCGAN++.
[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
This is the Pytorch implementation of "Learning Linear Transformations for Fast Image and Video Style Transfer" (CVPR 2019).
The unofficial implementation of LOGAN: Latent Optimisation for Generative Adversarial Networks
Tensorflow implementation of Disentangling Latent Space for VAE by Label Relevant/Irrelevant Dimensions (CVPR 2019)
침착한 생성모델 학습기
[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
GAN, transfer learning, few data.
Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
Improving MMD-GAN training with repulsive loss function
Open MMLab Image and Video Super-Resolution Toolbox, , including SRResNet, SRGAN, ESRGAN, EDVR, etc.
A Trimap-Free Solution for Portrait Matting in Real Time under Changing Scenes
MSG StyleGAN in tensorflow
MSGAN: Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis (CVPR2019)
PyTorch implementation of "Multi-marginal Wasserstein GAN" (NeurIPS2019)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.