lidar-point-cloud

The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"

KITTI Object Visualization (Birdview, Volumetric LiDar point cloud )

Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)

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

Implementation of SqueezeSeg, convolutional neural networks for LiDAR point clout segmentation

Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)

Intensity-based_Lidar_Camera_Calibration

Tool for convert files into Magicavoxel file

Use LiDAR to map the static world

C++ library and programs for reading and writing ASPRS LAS format with LiDAR data

A Modular Optimization framework for Localization and mApping (MOLA)

Implementation of SqueezeSegV2, Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

Lidar Obstacle Detection

Create Dense Depth Map Image for Known Poisitioned Camera from Lidar Point Cloud

A plugin for Grand Theft Auto V that generates a labeled LiDAR point cloud from the game environment.

Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion (AAAI 2021)

HELIOS - the Heidelberg LiDAR Operations Simulator - is a software package for interactive real-time simulation and visualisation of terrestrial, mobile and airborne laser scan surveys written in Java.

Visualizing lidar data using Uber Autonomous Visualization System (AVS) and Jupyter Notebook Application

Easy description to run and evaluate Lego-LOAM with KITTI-data

This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.

3D LiDAR annotation tool using ray tracing and bounding boxes.

The research project based on Semantic KITTTI dataset, 3d Point Cloud Segmentation , Obstacle Detection

This repository provides awesome research papers for autonomous driving perception. If you do find a problem or have any suggestions, please raise this as an issue or make a pull request with information (format of the repo): Research paper title, datasets, metrics, objects, source code, publisher, and year.

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

This repo detect objects automatically for LiDAR data

LiDAR fog simulation

Deep Lidar Inertial Odometry

Create 3D labelled bounding boxes in RViz