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Name: 刘国友
Type: User
Bio: xiaomi
Name: 刘国友
Type: User
Bio: xiaomi
[ICCV 2019]Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Transition
Implementation of the paper: StyleBank: An Explicit Representation for Neural Image Style Transfer
StyleFlow: Attribute-conditioned Exploration of StyleGAN-generated Images using Conditional Continuous Normalizing Flows
A PyTorch implementation for StyleGAN with full features.
StyleGAN2 - Official TensorFlow Implementation
PyTorch Implementation of In-Domain GAN Inversion for StyleGAN2
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
Official PyTorch implementation of StyleGAN3
Implementation for Paper "Inverting Generative Adversarial Renderer for Face Reconstruction"
StyleSwin: Transformer-based GAN for High-resolution Image Generation
Real-time neural style transfer via meta networks
风格迁移三部曲
Files to create the figures in the paper "Super-Convergence: Very Fast Training of Residual Networks Using Large Learning Rates"
The PyTorch implement of the paper "Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs"
Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch
SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
A fast and memory-optimized string library for C++
Towards Good Practice for CNN Based Monocular Depth Estimation
Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors
Code for the ICCV 2017 paper "Surface Normals in the Wild"
2020 TPAMI, SurfaceNet+ is a volumetric learning framework for the very sparse MVS. The sparse-MVS benchmark is maintained here. Authors: Mengqi Ji#, Jinzhi Zhang#, Qionghai Dai, Lu Fang.
Real-time surfel-based mesh reconstruction from RGB-D video.
self-supervised visibility learning for novel view synthesis, CVPR 2021
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.
Bottom-up Human Pose Estimation
30 mini Swift Apps for self-study
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.