daijicheng's repositories
3D-Machine-Learning
A learning resource repository for 3D machine learning
3DFeatNet
3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration
Attitude-Estimation
MatLAB and Python implementations for 6-DOF IMU attitude estimation using Kalman Filters, Complimentary Filters, etc.
awesome
:sunglasses: Curated list of awesome lists
BaiduPCS-Go
百度网盘客户端 - Go语言编写
CapsNet-Tensorflow
A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules
CGF
Code and data for "Learning Compact Geometric Features"
dlib
A toolkit for making real world machine learning and data analysis applications in C++
DynSLAM
Master's Thesis on Simultaneous Localization and Mapping in dynamic environments. Separately reconstructs both the static environment and the dynamic objects from it, such as cars.
FastGlobalRegistration
Fast Global Registration
ffn
Flood-Filling Networks for instance segmentation in 3d volumes.
fmt
A modern formatting library
GALGO-2.0
Genetic Algorithm in C++ with template metaprogramming and abstraction for constrained optimization
hdl_graph_slam
3D LIDAR-based Graph SLAM
IMUCalibration-Gesture
calibration for Imu and show gesture
kNN-CUDA
Fast k nearest neighbor search using GPU
LearnOpenGL-CN
http://learnopengl.com 系列教程的简体中文翻译
lidar_slam_3d
3d lidar slam package.
maplab
An open visual-inertial mapping framework.
ndt_omp
Multi-threaded and SSE friendly NDT algorithm
Open3D-PointNet2-Semantic3D
Semantic3D segmentation with Open3D and PointNet++
pointcloudToMesh
C++ application to convert pcd file, ply file, txt file or xyz point cloud to MESH representation (Gp3).
PointCNN
PointCNN
Recent_SLAM_Research
跟踪SLAM前沿动态【周更】
Run_based_segmentation
An ongoing implementation ros node on `fast segmentation of 3d point clouds: a paradigm`...
SAC-IA
Using PCL (Point Cloud Library) to Registration Point Cloud By SAC-IA, Initial Alignment
segmap
A map representation based on 3D segments
sparseicp
Automatically exported from code.google.com/p/sparseicp
state-of-the-art-result-for-machine-learning-problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.