137 Open source projects that are alternatives of or similar to Self Supervised Depth Completion

This repo detect objects automatically for LiDAR data

Self Driving Car Project 6 - Sensor Fusion(Extended Kalman Filter)

😎 Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators.

Official page of Patchwork (RA-L'21 w/ IROS'21)

LiDAR fog simulation

R package to read and write las and laz files used to store LiDAR data

open source slam system notes

Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI)

python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.

No description or website provided.

OpenDLV - A modern microservice-based software ecosystem powered by libcluon to make vehicles autonomous.

Online Range Image-based Pole Extractor for Long-term LiDAR Localization in Urban Environments

Development kit for Pandora

PyLidar3 is python 3 package to get data from Lidar devices from various manufacturers.

OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)

Collection of Python snippets for processing LiDAR point cloud.

UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes

Ros nodes for single TeraRanger sensors

Point cloud registration pipeline for robot localization and 3D perception

Open-Source LiDAR Time Synchronization System by Mimicking GPS-clock

Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗

GEDI L3 and L4 Tutorials

The open-source tool for creating of 3D models

pyGEDI is a Python Package for NASA's Global Ecosystem Dynamics Investigation (GEDI) mission, data extraction, analysis, processing and visualization.

A tool used for calibrate the extrinsic between 2D laser range finder (LRF) and camera. ROS Version: https://github.com/TurtleZhong/camera_lidar_calibration_v2

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks

Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform (RA-L)

Code for Langer et al. "Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks", IROS, 2020.

LiDAR SLAM = FAST-LIO + Scan Context

R package for airborne LiDAR data manipulation and visualisation for forestry application

State of the art autonomous navigation scripts using Ai, Computer Vision, Lidar and GPS to control an arducopter based quad copter.

T-LOAM: Truncated Least Squares Lidar-only Odometry and Mapping in Real-Time

My small SLAM simulator to study "SLAM for dummies"

Interactive Map Correction for 3D Graph SLAM

An extended Kalman Filter implementation in C++ for fusing lidar and radar sensor measurements.

Papers on 3D Object Detection for Autonomous Driving

GPS calibration using points cloud slam and other sensors

An extension of Open3D to address 3D Machine Learning tasks

An interactive GUI for WhiteboxTools in a Jupyter-based environment

Behind the Curtain: Learning Occluded Shapes for 3D Object Detection

TensorFlow training pipeline and dataset for prediction of evidential occupancy grid maps from lidar point clouds.

Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors.

This repository is an open-source PointPainting package which is easy to understand, deploy and run!

Filters: KF, EKF, UKF || Process Models: CV, CTRV || Measurement Models: Radar, Lidar

[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory

KITTI data processing and 3D CNN for Vehicle Detection

ROS package for NDT-PSO, a 2D Laser scan matching algorithm for SLAM

NCSU GIS595/MEA792: UAV/lidar Data Analytics

(ROS) Sensor fusion algorithm for camera+lidar.

LiDAR SLAM: Scan Context + LeGO-LOAM

MOLA module: Front-end for point-cloud sensors based on generic ICP algorithms. LiDAR odometry and loop closure.

ROS Catkin package to track people using octree and cluster extraction

Given a map data (image + lidar), estimate the 6 DoF camera pose of the query image.

VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS

Direct LiDAR Odometry: Fast Localization with Dense Point Clouds

SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)

The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.

Real-time 3D localization using a (velodyne) 3D LIDAR

Development kit for Pandar40

Probabilistic line extraction from 2-D range scan