310 Repositories
Python lidar-point-clouds Libraries
Score-Based Point Cloud Denoising (ICCV'21)
Score-Based Point Cloud Denoising (ICCV'21) [Paper] https://arxiv.org/abs/2107.10981 Installation Recommended Environment The code has been tested in
Direct LiDAR Odometry: Fast Localization with Dense Point Clouds
Direct LiDAR Odometry: Fast Localization with Dense Point Clouds DLO is a lightweight and computationally-efficient frontend LiDAR odometry solution w
A simple algorithm for extracting tree height in sparse scene from point cloud data.
TREE HEIGHT EXTRACTION IN SPARSE SCENES BASED ON UAV REMOTE SENSING This is the offical python implementation of the paper "Tree Height Extraction in
Adjust the white point, gamma or make your XDR display darker without losing HDR peak luminance or the ability to adjust display brightness
XDR Tuner Adjust the white point, gamma or make your XDR display darker without losing HDR peak luminance or the ability to adjust display brightness
Cooperative Driving Dataset: a dataset for multi-agent driving scenarios
Cooperative Driving Dataset (CODD) The Cooperative Driving dataset is a synthetic dataset generated using CARLA that contains lidar data from multiple
Small Robot, with LIDAR and DepthCamera. Using ROS for Maping and Navigation
🤖 RoboCop 🤖 Small Robot, with LIDAR and DepthCamera. Using ROS for Maping and Navigation Made by Clemente Donoso, 📍 Chile 🇨🇱 RoboCop Lateral Fron
Fast and robust clustering of point clouds generated with a Velodyne sensor.
Depth Clustering This is a fast and robust algorithm to segment point clouds taken with Velodyne sensor into objects. It works with all available Velo
Official implementation of Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models at NeurIPS 2021
Representer Point Selection via Local Jacobian Expansion for Classifier Explanation of Deep Neural Networks and Ensemble Models This repository is the
This is the face keypoint train code of project face-detection-project
face-key-point-pytorch 1. Data structure The structure of landmarks_jpg is like below: |--landmarks_jpg |----AFW |------AFW_134212_1_0.jpg |------AFW_
Pre-Training 3D Point Cloud Transformers with Masked Point Modeling
Point-BERT: Pre-Training 3D Point Cloud Transformers with Masked Point Modeling Created by Xumin Yu*, Lulu Tang*, Yongming Rao*, Tiejun Huang, Jie Zho
Semi-supervised Implicit Scene Completion from Sparse LiDAR
Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH
PyTorch implementation of Pointnet2/Pointnet++
Pointnet2/Pointnet++ PyTorch Project Status: Unmaintained. Due to finite time, I have no plans to update this code and I will not be responding to iss
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN
SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)
SuMa++: Efficient LiDAR-based Semantic SLAM This repository contains the implementation of SuMa++, which generates semantic maps only using three-dime
Kernel Point Convolutions
Created by Hugues THOMAS Introduction Update 27/04/2020: New PyTorch implementation available. With SemanticKitti, and Windows supported. This reposit
PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud, CVPR 2019.
PointRCNN PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud Code release for the paper PointRCNN:3D Object Proposal Generation a
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
OpenPCDet OpenPCDet is a clear, simple, self-contained open source project for LiDAR-based 3D object detection. It is also the official code release o
Semi-supervised Implicit Scene Completion from Sparse LiDAR
Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.
ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in
Spatial Sparse Convolution Library
SpConv: Spatially Sparse Convolution Library PyPI Install Downloads CPU (Linux Only) pip install spconv CUDA 10.2 pip install spconv-cu102 CUDA 11.1 p
Point Cloud Registration Network
PCRNet: Point Cloud Registration Network using PointNet Encoding Source Code Author: Vinit Sarode and Xueqian Li Paper | Website | Video | Pytorch Imp
Source code for Fixed-Point GAN for Cloud Detection
FCD: Fixed-Point GAN for Cloud Detection PyTorch source code of Nyborg & Assent (2020). Abstract The detection of clouds in satellite images is an ess
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)
Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes [Paper] Method overview 4DMatch Benchmark 4DMatch is a benchmark for matc
A Collection of LiDAR-Camera-Calibration Papers, Toolboxes and Notes
A Collection of LiDAR-Camera-Calibration Papers, Toolboxes and Notes
Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion"
DSPoint Official implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion". Paper link: https://arxiv.org/abs/2111.10
A hybrid SOTA solution of LiDAR panoptic segmentation with C++ implementations of point cloud clustering algorithms. ICCV21, Workshop on Traditional Computer Vision in the Age of Deep Learning
ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)
Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe
Real-time ground filtering algorithm of cloud points acquired using Terrestrial Laser Scanner (TLS)
This repository contains tools to simulate the ground filtering process of a registered point cloud. The repository contains two filtering methods. The first method uses a normal vector, and fit to plane. The second method utilizes voxel adjacency, and fit to plane.
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place
Ultra-lightweight human body posture key point CNN model. ModelSize:2.3MB HUAWEI P40 NCNN benchmark: 6ms/img,
Ultralight-SimplePose Support NCNN mobile terminal deployment Based on MXNET(=1.5.1) GLUON(=0.7.0) framework Top-down strategy: The input image is t
Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion"
DSPoint Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion" Coming soon, as soon as I finish a
An improvement of FasterGICP: Acceptance-rejection Sampling based 3D Lidar Odometry
fasterGICP This package is an improvement of fast_gicp Please cite our paper if possible. W. Jikai, M. Xu, F. Farzin, D. Dai and Z. Chen, "FasterGICP:
Some method of processing point cloud
Point-Cloud Some method of processing point cloud inversion the completion pointcloud to incomplete point cloud Some model of encoding point cloud to
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.
counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code
RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation
RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation Anonymous submission Abstract 3D obj
A robust camera and Lidar fusion based velocity estimator to undistort the pointcloud.
Lidar with Velocity A robust camera and Lidar fusion based velocity estimator to undistort the pointcloud. related paper: Lidar with Velocity : Motion
Unofficial implementation of Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation
Point-Unet This is an unofficial implementation of the MICCAI 2021 paper Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segment
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks This is a Pytorch-Lightning implementation of the paper "Self-s
Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
DD3D: "Is Pseudo-Lidar needed for Monocular 3D Object detection?" Install // Datasets // Experiments // Models // License // Reference Full video Offi
Clip Bing Maps backgound as RGB geotif image using center-point from vector data of a shapefile and Bing Maps zoom
Clip Bing Maps backgound as RGB geotif image using center-point from vector data of a shapefile and Bing Maps zoom. Also, rasterize shapefile vectors as corresponding label image.
Object detection, 3D detection, and pose estimation using center point detection:
Objects as Points Object detection, 3D detection, and pose estimation using center point detection: Objects as Points, Xingyi Zhou, Dequan Wang, Phili
PyTorch Code for "Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning"
Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning [Project Page] [Paper] Wenlong Huang1, Igor Mordatch2, Pieter Abbeel1,
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages Abstract NLP applications for code-mixed (CM) or mix-li
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.
counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code
Point detection through multi-instance deep heatmap regression for sutures in endoscopy
Suture detection PyTorch This repo contains the reference implementation of suture detection model in PyTorch for the paper Point detection through mu
PSANet: Point-wise Spatial Attention Network for Scene Parsing, ECCV2018.
PSANet: Point-wise Spatial Attention Network for Scene Parsing (in construction) by Hengshuang Zhao*, Yi Zhang*, Shu Liu, Jianping Shi, Chen Change Lo
Weakly Supervised 3D Object Detection from Point Cloud with Only Image Level Annotation
SCCKTIM Weakly Supervised 3D Object Detection from Point Cloud with Only Image-Level Annotation Our code will be available soon. The class knowledge t
A tool for automatically generating 3D printable STLs from freely available lidar scan data.
mini-map-maker A tool for automatically generating 3D printable STLs from freely available lidar scan data. Screenshots Tutorial To use this script, g
Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation".
FPS-Net Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation", accepted by ISPRS journal of Photogrammetry
Computationally efficient algorithm that identifies boundary points of a point cloud.
BoundaryTest Included are MATLAB and Python packages, each of which implement efficient algorithms for boundary detection and normal vector estimation
6D Grasping Policy for Point Clouds
GA-DDPG [website, paper] Installation git clone https://github.com/liruiw/GA-DDPG.git --recursive Setup: Ubuntu 16.04 or above, CUDA 10.0 or above, py
This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods
pyLiDAR-SLAM This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods, which can easily be evaluated
[ICCV 2021] HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration
HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration Introduction The repository contains the source code and pre-tr
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving (ICCV 2021)
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving Chenxu Luo, Xiaodong Yang, Alan Yuille Exploring Simple 3D Multi-Object Tracking for
Perception-aware multi-sensor fusion for 3D LiDAR semantic segmentation (ICCV 2021)
Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation (ICCV 2021) [中文|EN] 概述 本工作主要探索一种高效的多传感器(激光雷达和摄像头)融合点云语义分割方法。现有的多传感器融合方法主要将点云投影
[ICCV' 21] "Unsupervised Point Cloud Pre-training via Occlusion Completion"
OcCo: Unsupervised Point Cloud Pre-training via Occlusion Completion This repository is the official implementation of paper: "Unsupervised Point Clou
A wrapper for webdriver that is a jumping off point for web automation.
Webdriver Automation Plus ===================================== Description: Tests the user can save messages then find them in search and Saved items
Codes for CVPR2021 paper "PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization"
PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization (CVPR 2021) This is the official implementation of PW
code for Fast Point Cloud Registration with Optimal Transport
robot This is the repository for the paper "Accurate Point Cloud Registration with Robust Optimal Transport". We are in the process of refactoring the
An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance"
Lidar-Segementation An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021]
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng
Pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021).
Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested
Cloudkeeper is “housekeeping for clouds” - find leaky resources, manage quota limits, detect drift and clean up.
Cloudkeeper Housekeeping for Clouds! Table of contents Overview Docker based quick start Cloning this repository Component list Contact License Overvi
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration (NeurIPS 2021) PyTorch implementation of the paper: CoFiNet: Reli
This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape
Metashape-Utils This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape, given a set of 2D coordinates
UI for converting various point cloud file formats
Point cloud format converter This coverter based on open3d. If you're using old ROS1 i suggest to use conda python3 evn to install requirements. Todo
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"
The official codes for the ICCV2021 Oral presentation "Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework"
P2PNet (ICCV2021 Oral Presentation) This repository contains codes for the official implementation in PyTorch of P2PNet as described in Rethinking Cou
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching This is our attempt of the shared task on Quan
Visualize the electric field of a point charge network.
ElectriPy ⚡ Visualize the electric field of a point charges network. 🔌 Installation Install ElectriPy package: $ pip install electripy You are all d
A LiDAR point cloud cluster for panoptic segmentation
Divide-and-Merge-LiDAR-Panoptic-Cluster A demo video of our method with semantic prior: More information will be coming soon! As a PhD student, I don'
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"
MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori
Official PyTorch code for the paper: "Point-Based Modeling of Human Clothing" (ICCV 2021)
Point-Based Modeling of Human Clothing Paper | Project page | Video This is an official PyTorch code repository of the paper "Point-Based Modeling of
Cascading Feature Extraction for Fast Point Cloud Registration (BMVC 2021)
Cascading Feature Extraction for Fast Point Cloud Registration This repository contains the source code for the paper [Arxive link comming soon]. Meth
This is an official source code for implementation on Extensive Deep Temporal Point Process
Extensive Deep Temporal Point Process This is an official source code for implementation on Extensive Deep Temporal Point Process, which is composed o
Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"
About this repository This repo contains an Pytorch implementation for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Netwo
Points2Surf: Learning Implicit Surfaces from Point Clouds (ECCV 2020 Spotlight)
Points2Surf: Learning Implicit Surfaces from Point Clouds (ECCV 2020 Spotlight)
DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction (3DV 2021)
DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction (3DV 2021) This repo is the implementation of DPC. Tested environment Pyth
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression Overview The ever-increasing 3D application makes the point cloud compression unprec
Official PyTorch implementation of PICCOLO: Point-Cloud Centric Omnidirectional Localization (ICCV 2021)
Official PyTorch implementation of PICCOLO: Point-Cloud Centric Omnidirectional Localization (ICCV 2021)
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
This repository contains the code accompanying the paper " FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation" Paper link: R
Benchmark tools for Compressive LiDAR-to-map registration
Benchmark tools for Compressive LiDAR-to-map registration This repo contains the released version of code and datasets used for our IROS 2021 paper: "
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"
DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re
ADOP: Approximate Differentiable One-Pixel Point Rendering
ADOP: Approximate Differentiable One-Pixel Point Rendering Abstract: We present a novel point-based, differentiable neural rendering pipeline for scen
Official Implementation (PyTorch) of "Point Cloud Augmentation with Weighted Local Transformations", ICCV 2021
PointWOLF: Point Cloud Augmentation with Weighted Local Transformations This repository is the implementation of PointWOLF(To appear). Sihyeon Kim1*,
Continuous Conditional Random Field Convolution for Point Cloud Segmentation
CRFConv This repository is the implementation of "Continuous Conditional Random Field Convolution for Point Cloud Segmentation" 1. Setup 1) Building c
Continuous Time LiDAR odometry
CT-ICP: Elastic SLAM for LiDAR sensors This repository implements the SLAM CT-ICP (see our article), a lightweight, precise and versatile pure LiDAR o
Posterior predictive distributions quantify uncertainties ignored by point estimates.
Posterior predictive distributions quantify uncertainties ignored by point estimates.
Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021.
SphereRPN Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021. Authors: Th
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021)
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is
[ICCV 2021 Oral] SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
This repository contains the source code for the paper SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer (ICCV 2021 Oral). The project page is here.
Uses WiFi signals :signal_strength: and machine learning to predict where you are
Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.
Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR
Official implementation for paper "Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR"
GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
GndNet: Fast Ground plane Estimation and Point Cloud Segmentation for Autonomous Vehicles. Authors: Anshul Paigwar, Ozgur Erkent, David Sierra Gonzale
PyTorch implementation for View-Guided Point Cloud Completion
PyTorch implementation for View-Guided Point Cloud Completion
Float2Binary - A simple python class which finds the binary representation of a floating-point number.
Float2Binary A simple python class which finds the binary representation of a floating-point number. You can find a class in IEEE754.py file with the
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021)
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021) This repository contains the code