lidar-camera-fusion
There are 19 repositories under lidar-camera-fusion topic.
hku-mars / FAST-LIVO2
FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry
Language:C++ 2765A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
Language:C++ 2247- Language:C++ 1445
Deephome / Awesome-LiDAR-Camera-Calibration
A Collection of LiDAR-Camera-Calibration Papers, Toolboxes and Notes
- xtreme1
xtreme1-io / xtreme1
Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.
Language:TypeScript 1067 EPVelasco / lidar-camera-fusion
The code implemented in ROS projects a point cloud obtained by a Velodyne VLP16 3D-Lidar sensor on an image from an RGB camera.
Language:C++ 293PJLab-ADG / LoGoNet
[CVPR2023] LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion
Language:Python 270SxJyJay / MSMDFusion
[CVPR 2023] MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection
Language:Python 189HITSZ-NRSL / lidar_camera_calibrator
ROS package to calibrate the extrinsic parameters between LiDAR and Camera.
Language:C++ 181xmba15 / automatic_lidar_camera_calibration
auto-calibration of lidar and camera based on maximization of intensity mutual information
Language:C++ 125KleinYuan / LiCaS3
[T-RO 2022] Official Implementation for "LiCaS3: A Simple LiDAR–Camera Self-Supervised Synchronization Method," in IEEE Transactions on Robotics, doi: 10.1109/TRO.2022.3167455.
Language:Python 91ika-rwth-aachen / MultiCorrupt
[IV2024] MultiCorrupt: A benchmark for robust multi-modal 3D object detection, evaluating LiDAR-Camera fusion models in autonomous driving. Includes diverse corruption types (e.g., misalignment, miscalibration, weather) and severity levels. Assess model performance under challenging conditions.
Language:Jupyter Notebook 61GCaptainNemo / Fusion-Lidar-Camera-ROS
This repository uses a ROS node to subscribe to camera (hikvision) and lidar (livox) data. After the node merges the data, it publishes the colored point cloud and displays it in rviz.
Language:C++ 55AdroitAnandAI / ADAS-Car-using-Raspberry-Pi
ADAS Car - with Collision Avoidance System (CAS) - on Indian Roads using LIDAR-Camera Low-Level Sensor Fusion. DIY Gadget built with Raspberry Pi, RP LIDAR A1, Pi Cam V2, LED SHIM, NCS 2 and accessories like speaker, power bank etc
Language:Python 39Lidar Camera Manual Target-less Calibration Software
Language:Python 22- Language:Python 19
Extrinsic Calibration of Monocular Camera and Lidar using Planar Point To Plane Constraint
Language:Python 13UMich-BipedLab / global_pose_estimation_for_optimal_shape
This package introduces the concept of optimizing target shape to remove pose ambiguity for LiDAR point clouds. Both the simulation and the experimental results confirm that by using the optimal shape and the global solver, we achieve centimeter error in translation and a few degrees in rotation even when a partially illuminated target is placed 30 meters away!
Language:MATLAB 11harrylal / simulation-of-birds-eye-view-map-generation-from-rgbd-data
Project: Generating overhead birds-eye-view occupancy grid map with semantic information from lidar and camera data.
Language:Python 10m-shahbaz-kharal / LiGuard-JOSS
A research-purposed, GUI-powered, Python-based framework that allows easy development of dynamic point-cloud (and accompanying image) data processing pipelines.
Language:Python 5- ATM-SfM-Bathymetry
mstudinger / ATM-SfM-Bathymetry
This repository contains tools for deriving supraglacial lake bathymetry from ATM aerial imagery using the Ames Stereo Pipeline.
Language:Jupyter Notebook 5 simple visualization toolbox for 3d vision sensors/tasks
Language:Python 4beamaginelidar / l3cam_fusion
ROS2 package for the visualization of the fusion of the L3Cam device sensors
Language:C++ 2ROS2 package that integrates L3CAM sensors using L3CAM SDK
Language:C++ 2BigTeacher-777 / Awesome-Multi-Modal-3D-Detection
Awesome Multi-Modal 3D Detection
This package introduces the concept of optimizing target shape to remove pose ambiguity for LiDAR point clouds. Both the simulation and the experimental results confirm that by using the optimal shape and the global solver, we achieve centimeter error in translation and a few degrees in rotation even when a partially illuminated target is placed 30 meters away!
Language:MATLAB 2- Language:C++ 1
- Language:C 1
- Language:C++ 1
A research-purposed, GUI-powered, Python-based framework that allows easy development of dynamic point-cloud (and accompanying image) data processing pipelines.
Language:Python 1This repository contains MATLAB® functions for deriving supraglacial lake bathymetry from ATM laser altimetry data products
Language:MATLAB 0
