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Name: 刘国友
Type: User
Bio: xiaomi
Name: 刘国友
Type: User
Bio: xiaomi
Normalization Matters in Weakly Supervised Object Localization (ICCV 2021)
Implementation of RAISR (Rapid and Accurate Image Super Resolution) algorithm in Python 3.x by Jalali Laboratory at UCLA. The implementation presented here achieved performance results that are comparable to that presented in Google's research paper (with less than ± 0.1 dB in PSNR). Just-in-time (JIT) compilation employing JIT numba is used to speed up the Python code. A very parallelized Python code employing multi-processing capabilities is used to speed up the testing process. The code has been tested on GNU/Linux and Mac OS X 10.13.2 platforms.
This is the code for CVPR 2021 oral paper: Jigsaw Clustering for Unsupervised Visual Representation Learning
An unofficial implementation of Joint Bilateral Learning for Real-time Universal hotorealistic Style Transfer
Code for ICIP 2017 paper JOINT DEMOSAICING AND DENOISING OF NOISY BAYER IMAGES WITH ADMM
This rerpo is an implementation of the paper "Multi-exposure Fusion With JPEG Compression Guidance" on VCIP2018.
Code for "Joint Voxel and Coordinate Regression for Accurate 3D Facial Landmark Localization"
Image Restoration Toolbox (PyTorch). Training and testing codes for DnCNN, FFDNet, SRMD, DPSR, MSRResNet, ESRGAN, IMDN
A PyTorch Library for Accelerating 3D Deep Learning Research
Tool for automating common video keyframe extraction and Image Autocrop tasks
High-Speed Tracking with Kernelized Correlation Filters
python implementation of "high-speed tracking with kernelized correlation filters"
C++ Implementation of KCF Tracker
Repository for 《A Distillation Framework for Accurate and Robust Single View 3D Face Reconstruction with Video Supervision》
EDSR, RCAN, SRGAN, SRFEAT, ESRGAN
Keras Implementation of MixNets: Mixed Depthwise Convolutions
Keras implementation of R-MAC+ descriptors
Official Implementation for Kernel Modeling Super-Resolution on Real Low-Resolution Images
Reimplement of 'Burst Denoising with Kernel Prediction Networks' and 'Multi-Kernel Prediction Networks for Denoising of Image Burst' by using PyTorch
A library for converting Adobe AE shape based animations to a data format and playing it back on Android and iOS devices.
KFNet: Learning Temporal Camera Relocalization using Kalman Filtering (CVPR 2020 Oral)
Fast, modern C++ DSP framework, FFT, Audio Sample Rate Conversion, FIR/IIR/Biquad Filters (SSE, AVX, ARM NEON)
Code for: "And the bit goes down: Revisiting the quantization of neural networks"
Kindling the Darkness: a Practical Low-light Image Enhancer
Beyond Brightening Low-light Images
Python implementation of KNN Matting, CVPR 2012 / TPAMI 2013 http://dingzeyu.li/projects/knn/
ICIP 2020, FAKD: Feature-Affinity Based Knowledge Distillation for Efficient Image Super-Resolution
Open Source Differentiable Computer Vision Library for PyTorch
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.