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3d-lidar-multi-object-tracking

🔥3D-MOT(点云多目标检测和追踪C++) （2020 · 秋） 代码有详细注解

3d-point-clouds

🔥3D点云目标检测&语义分割(深度学习)-SOTA方法,代码,论文,数据集等

apollo_perception_ros

Object detection / tracking / fusion based on Apollo r3.0.0 perception module in ROS

autoware.universe

awesome-data-labeling-tools

图像images/点云point clouds标注工具汇总

carnd-extended-kalman-filter-project

Self-Driving Car Nanodegree Program Starter Code for the Extended Kalman Filter Project

datmo

Detection and Tracking of Moving Objects (DATMO) using sensor_msgs/Lidar.

depth_clustering

:taxi: Fast and robust clustering of point clouds generated with a Velodyne sensor.

dynamic-occupancy-grid-map

Implementation of "A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application"

elevation_mapping

Robot-centric elevation mapping for rough terrain navigation

grid_map

Universal grid map library for mobile robotic mapping

kalman

Some Python Implementations of the Kalman Filter

kalman_filters

Header only C++ implementation of standard and extended Kalman filters.

lidar-segementation

An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from IROS 2019

lidar_for_ad_references

A list of references on lidar point cloud processing for autonomous driving

lidar_obstacle_detector

3D LiDAR Object Detection & Tracking using Euclidean Clustering, RANSAC, & Hungarian Algorithm

lidarobstacledetection

Lidar Obstacle Detection

linefit_ground_segmentation

Ground Segmentation

mmdetection3d

OpenMMLab's next-generation platform for general 3D object detection.

mmdetection3d-note

mmdetection3d 代码重点注解笔记

multi-object-tracking

A fast object tracking method by using JPDA-IMM-UKF.

multi-sensor-fusion

多传感器融合（lidar radar camera）

multilayer-stixel-world

An implementation of multi-layered stixel computation

multiple-object-tracking-lidar

C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud

nutonomy_pointpillars

Convert pointpillars Pytorch Model To ONNX for TensorRT Inference

object-detection-in-point-cloud-road-boundary

Object detection in Point Cloud is popular in HD Map and sensor-based autonomous driving. There basically four types of object you can obtain in daily scenario: road surface - contains painted lane marking and pavement area, support facility - contains road boundary (guardrail and curb), road sign, light pole, etc., uncorrelated object - for example, sidewalk, building, etc., and moving object - such like pedestrian, vehicle, bicycle, etc. In this project, please search references, design and prototype your road boundary (guardrail) detection algorithm.

object_builders_lib

Object Orientation Corrected Bounding Box Fit for Point Cloud Clusters.

obstacle_detector

A ROS package for 2D obstacle detection based on laser range data.

patchwork-plusplus-ros

ROS Implementation of Patchwork++

plane_fit_ground_filter-1

A point cloud ground filter based on ground plane fitting