cloud to mapAlgorithm that converts point cloud data into an occupancy grid
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PclPoint Cloud Library (PCL)
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Depth clustering🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.
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Point Cloud FilterScripts showcasing filtering techniques applied to point cloud data.
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Fast gicpA collection of GICP-based fast point cloud registration algorithms
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Ndt ompMulti-threaded and SSE friendly NDT algorithm
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pcl.pyTemplated python inferface for Point Cloud Library (PCL) based on Cython
Stars: ✭ 64 (+100%)
pcljavaA port of the Point Cloud Library (PCL) using Java Native Interface (JNI).
Stars: ✭ 19 (-40.62%)
Lidar camera calibrationLight-weight camera LiDAR calibration package for ROS using OpenCV and PCL (PnP + LM optimization)
Stars: ✭ 133 (+315.63%)
PclpyPython bindings for the Point Cloud Library (PCL)
Stars: ✭ 212 (+562.5%)
geometric advGeometric Adversarial Attacks and Defenses on 3D Point Clouds (3DV 2021)
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fastremapRemap, mask, renumber, unique, and in-place transposition of 3D labeled images. Point cloud too.
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e3dEfficient 3D Deep Learning
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superpose3dregister 3D point clouds using rotation, translation, and scale transformations.
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SpareNetStyle-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)
Stars: ✭ 118 (+268.75%)
roofn3dRoof Classification, Segmentation, and Damage Completion using 3D Point Clouds
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annotateCreate 3D labelled bounding boxes in RViz
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MinkLocMultimodalMinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
Stars: ✭ 65 (+103.13%)
NeuralPullImplementation of ICML'2021:Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces
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Displaz.jlJulia bindings for the displaz lidar viewer
Stars: ✭ 16 (-50%)
Depth-Guided-InpaintingCode for ECCV 2020 "DVI: Depth Guided Video Inpainting for Autonomous Driving"
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PointCutMixour code for paper 'PointCutMix: Regularization Strategy for Point Cloud Classification'
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mix3dMix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021 Oral)
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3D Ground SegmentationA ground segmentation algorithm for 3D point clouds based on the work described in “Fast segmentation of 3D point clouds: a paradigm on LIDAR data for Autonomous Vehicle Applications”, D. Zermas, I. Izzat and N. Papanikolopoulos, 2017. Distinguish between road and non-road points. Road surface extraction. Plane fit ground filter
Stars: ✭ 55 (+71.88%)
attMPTI[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation
Stars: ✭ 118 (+268.75%)
gitter-api-pclGitter# provide you the minimum code you need to use the Gitter API
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Point2MeshMeshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance (ECCV2020)
Stars: ✭ 61 (+90.63%)
pcl localization ros2ROS2 package of 3D LIDAR-based Localization using PCL (Not SLAM)
Stars: ✭ 74 (+131.25%)
realsense explorer botAutonomous ground exploration mobile robot which has 3-DOF manipulator with Intel Realsense D435i mounted on a Tracked skid-steer drive mobile robot. The robot is capable of mapping spaces, exploration through RRT, SLAM and 3D pose estimation of objects around it. This is an custom robot with self built URDF model.The Robot uses ROS's navigation…
Stars: ✭ 61 (+90.63%)
SGGpoint[CVPR 2021] Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis (official pytorch implementation)
Stars: ✭ 41 (+28.13%)
simpleICPImplementations of a rather simple version of the Iterative Closest Point algorithm in various languages.
Stars: ✭ 140 (+337.5%)
ldgcnnLinked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features
Stars: ✭ 66 (+106.25%)
WS3DOfficial version of 'Weakly Supervised 3D object detection from Lidar Point Cloud'(ECCV2020)
Stars: ✭ 104 (+225%)
Scan2Cap[CVPR 2021] Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
Stars: ✭ 81 (+153.13%)
Flownet3dFlowNet3D: Learning Scene Flow in 3D Point Clouds (CVPR 2019)
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Spvnas[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
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iros bshotB-SHOT : A Binary Feature Descriptor for Fast and Efficient Keypoint Matching on 3D Point Clouds
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PcnCode for PCN: Point Completion Network in 3DV'18 (Oral)
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AsisAssociatively Segmenting Instances and Semantics in Point Clouds, CVPR 2019
Stars: ✭ 228 (+612.5%)
RINDNetRINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth, in ICCV 2021 (oral)
Stars: ✭ 74 (+131.25%)
3D object recognitionrecognize and localize an object in 3D Point Cloud scene using VFH - SVMs based method and 3D-CNNs method
Stars: ✭ 91 (+184.38%)
CupochRobotics with GPU computing
Stars: ✭ 225 (+603.13%)
Cylinder3dRank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)
Stars: ✭ 221 (+590.63%)
deepedgedeep learning edge detector based on U-net and BSDS 500 dataset
Stars: ✭ 25 (-21.87%)