Awesome Open Source
Search
Programming Languages
Languages
All Categories
Categories
About
Search results for 2d graphics point cloud
2d-graphics
x
point-cloud
x
0 search results found
Frustum Pointnets
⭐
974
Frustum PointNets for 3D Object Detection from RGB-D Data
3d Bat
⭐
414
3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling
Polylidar
⭐
189
Polylidar3D - Fast polygon extraction from 3D Data
Npyviewer
⭐
104
Load and view .npy files containing 2D and 1D NumPy arrays.
Cloudtogrid
⭐
76
Example of converting a 2d point cloud to a 2d grid via the assignment problem.
Costmap_depth_camera
⭐
55
This is a costmap plugin for costmap_2d pkg. This plugin supports multiple depth cameras and run in real time.
Semanticmvs
⭐
31
Semantic 3D Reconstruction with Learning MVS and 2D Segmentation of Aerial Images, Applied Sciences 2021
3d Bounding Boxes From Monocular Images
⭐
15
A two stage multi-modal loss model along with rigid body transformations to regress 3D bounding boxes
Pcp
⭐
14
label KITTI point cloud (3d) drivable area using provided image annotations (2d)
Google Cartographer Slam With Velodyne16
⭐
10
3d_mapping_based_on_2d_lidar_along_motion
⭐
8
This repository is established as part of master thesis work. The 3D mapping is done with 2 2D lidar sensors and imu, one lidar used for 2D localization, the other for mapping, imu for heading estimation
Depthcam_hector_slam
⭐
8
a fusion of Hector SLAM 2d map construction and depth camera's pointcloud data
Pyrgbd
⭐
8
python RGB-D processing tool
Gl Pointcloud2d
⭐
8
2D point cloud
Antsy2d
⭐
6
in-browser point cloud annotation tool for instance-level segmentation using 2d projection
Pcl Normal Estimation 2d
⭐
6
PCL add-on to compute normal estimation to 2D pointCloud
Pmnet
⭐
5
We design an end-to-end deep neural network architecture for LiDAR point cloud and 2D image point-wise feature fusion, which is suitable for directly consuming unordered point cloud. To the best of our knowledge, this is the first approach to use multimodal fusion network for aerial point cloud 3D segmentation which well respects the permutation invariance of point cloud. PMNet has an advantage over 2D based models that it can incorporate multi-view 3D scanned data if available.
1-0 of 0 search results
Privacy
|
About
|
Terms
|
Follow Us On Twitter
Copyright 2018-2024 Awesome Open Source. All rights reserved.