chengshuai1992 Goto Github PK
Name: Shuai Cheng
Type: User
Name: Shuai Cheng
Type: User
The implementation of AAAI-17 paper "Collective Deep Quantization of Efficient Cross-modal Retrieval"
code of our work : Adaptive Exploration for Unsupervised Person Re-Identification
The code of ADE
Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning (CVPR 2017)
Unofficial implementation of "Max-margin Class Imbalanced Learning with Gaussian Affinity"
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
All about attention in neural networks. Soft attention, attention maps, local and global attention and multi-head attention.
📝Awesome and classical image retrieval papers
A comprehensive list of awesome contrastive self-supervised learning papers.
An awesome paper list of Semi-Supervised Learning under realistic settings.
:scroll: A curated list of awesome semi-supervised learning methods & papers.
papers collection and understanding for video person re-identification
People apply Bayesian methods in many areas: from game development to drug discovery. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. Bayesian methods also allow us to estimate uncertainty in predictions, which is a desirable feature for fields like medicine. When applied to deep learning, Bayesian methods allow you to compress your models a hundred folds, and automatically tune hyperparameters, saving your time and money. In six weeks we will discuss the basics of Bayesian methods: from how to define a probabilistic model to how to make predictions from it. We will see how one can automate this workflow and how to speed it up using some advanced techniques. We will also see applications of Bayesian methods to deep learning and how to generate new images with it. We will see how new drugs that cure severe diseases be found with Bayesian methods.
Action recognition with C3D network implemented in tensorflow
A simple Tensorflow code for C3D
connect cassandra database
Non-official implement of Paper:CBAM: Convolutional Block Attention Module
《CBAM: Convolutional Block Attention Module》 pytorch实现
Personal blog based on Hexo
Creat your own dataset with the similar format with CIFAR10 in python version.
Paper implementation
Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
This repository contains the code for our paper "Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization"
Code for the paper "Contrastive Clustering" (AAAI 2021)
Experiments with supervised contrastive learning methods with different loss functions
The source code for the paper: Yirong Mao, Ruiping Wang, Shiguang Shan, Xilin Chen. COSONet: Compact Second-Order Network for Video Face Recognition. ACCV 2018
The implementation of CVPR-17 paper "Deep Visual-Semantic Quantization of Efficient Image Retrieval"
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.