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Name: hanliming
Type: User
Bio: [email protected]
Name: hanliming
Type: User
Bio: [email protected]
Implementation of ECCV'18 paper - GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
GROR:A New Outlier Removal Strategy Based on Reliability of Correspondence Graph for Fast Point Cloud Registration
A General Simultaneous Localization and Mapping Framework which supports feature based or direct method and different sensors including monocular camera, RGB-D sensors or any other input types can be handled.
From Coarse to Fine: Robust Hierarchical Localization at Large Scale with HF-Net (https://arxiv.org/abs/1812.03506)
Visual localization made easy
Human-in-the-Loop SLAM
HTMap: Hierarchical Topological Mapping
This is a toolbox repository to help evaluate various methods that perform image matching from a pair of images.
A compact package for undistorting images directly from kalibr calibration files. Can also perform dense stereo estimation
Intensity Scan Context based full SLAM implementation for autonomous driving.
A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.
The lattice_planner package provides a move_base global planner plugin for a time-bounded A* lattice planner. The planner is designed to plan time dependent, dynamically feasible navigation paths for robots with differential drive constraints. It uses a dynamic cost map which is based on the ROS costmap representation from the costmap_2d package.
DSO with SIM(3) pose graph optimization and loop closure
A simple method for finding the extrinsic calibration between a 3D lidar and a 6-dof pose sensor
Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Lidar Odometry and Mapping with Mutiple Metrics Linear Least Square ICP
Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021
周志华《机器学习》又称西瓜书是一本较为全面的书籍,书中详细介绍了机器学习领域不同类型的算法(例如:监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等),记录了本人在学习过程中的理解思路与扩展知识点,希望对新人阅读西瓜书有所帮助!
A general framework for map-based visual localization. It contains 1) Map Generation which support traditional features or deeplearning features. 2) Hierarchical-Localizationvisual in visual(points or line) map. 3)Fusion framework with IMU, wheel odom and GPS sensors.
定位及高精地图技术文档
Multi primitive-to-primitive (MP2P) ICP algorithms in C++
Odom intrinsic and odom-sensors extrinsic calibration on SE2 using batch optimization.
An open source platform for visual-inertial navigation research.
OpenVSLAM: A Versatile Visual SLAM Framework
Modified ORB-SLAM2 to run on dual cameras (without common-view)
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose (CVPR 2021)
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.