There are 25 repositories under point-cloud-segmentation topic.
A list of papers and datasets about point cloud analysis (processing)
[CVPR'23] OpenScene: 3D Scene Understanding with Open Vocabularies
Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation (CVPR 2022)
Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering"
[ROS package] Lightweight and Accurate Point Cloud Clustering
[CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"
A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways
GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds."
Achelous: A Fast Unified Water-surface Panoptic Perception Framework based on Fusion of Monocular Camera and 4D mmWave Radar
Fast and memory efficient semantic segmentation of 3D point clouds. Runs on Windows, Mac and Linux.
[IROS23] InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data
Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features
The research project based on Semantic KITTTI dataset, 3d Point Cloud Segmentation , Obstacle Detection
Minimum code needed to run Autoware multi-object tracking
Semantic 3D Reconstruction with Learning MVS and 2D Segmentation of Aerial Images, Applied Sciences 2021
Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation (MICCAI 2021)
Semantic Segmentation of Images and Point Clouds for Traversability Estimation
Deep Learning for Computer Vision 深度學習於電腦視覺 by Frank Wang 王鈺強
ICCV 2021 papers and code focus on point cloud analysis
Trying to compute the completeness of a 3D map and compare it to another 3D map in a pointcloud format
Improved pytorch implementation of RandLA (https://arxiv.org/abs/1911.11236) with easier transferability and reproductibility
Point cloud segmentation with Azure Kinect
A High-Efficient Research Development Toolkit for Image Segmentation Based on Pytorch.
3D Human Part Segmentation with Point Transformer
Python scripts for converting mesh formats, mesh simplification and mesh rigid transformation
FLS point cloud registration library.
In this project we detect, segment and track the obstacles of an ego car and its custom implementation of KDTree, obstacle detection, segmentation, clustering and tracking algorithm in C++ and compare it to the inbuilt algorithm functions of PCL library on a LiDAR's point cloud data.
PCD annotation processing and guideline based on Semantic Segmentation Editor
Final project titled "Point Cloud Segmentation and Object Tracking using RGB-D Data" for the Machine Vision (EE 576) course.
This is a repository mainly about IEEE data fusion contest 2019 track 4 — Cloud points classification
Dash Robotics Perception
Implementation of point transformer for point cloud classification and segmentation
Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving
3D Teeth Scan Segmentation via Rotation-Invariant Descriptor
Implementing a PointNet based architecture for classification and segmentation with point clouds. Q1 and Q2 focus on implementing, training and testing models. Q3 asks you to quantitatively analyze model robustness.