akharroubi

Abderrazzaq KHARROUBI 's starred repositories

superpoint_transformer

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"

Language:PythonMIT52700

3D-Data-Essentials

3D DATA PROCESSING AND MODELING ESSENTIALS: A curated collection of tools, literature, courses, and datasets for mastering 3D point cloud technology.

3200

Rail3D

Rail3D: Multi-Context Point Cloud Dataset and New Approach for Railways Semantic Understanding

Language:Python2100

segment-lidar

Python package for segmenting LiDAR data using Segment-Anything Model (SAM) from Meta AI.

Language:PythonBSD-3-Clause31900

SemanticML

A package for semantic segmentation of 3D unorganized point clouds using Machine Learning techniques.

Language:PythonBSD-3-Clause900

Optim3D

Command-Line Interface (CLI) application for efficient and scalable generation of large-scale 3D building models.

Language:PythonBSD-3-Clause2500

ZRect3D

Command-Line Interface (CLI) application to automatically correct buildings ground-floor elevation in 3D city models.

Language:PythonBSD-3-Clause500

Tesserae3D

TESSERAE3D: A BENCHMARK FOR TESSERAE SEMANTIC SEGMENTATION IN 3D POINT CLOUDS

Apache-2.0200

RF4PCC

RF4PCC: Random Forest 4 Point Cloud Classification, 3DOM FBK

Language:Python1400

GeoSoft

A repository for geospatial software

MIT100

Open3D

Open3D: A Modern Library for 3D Data Processing

Language:C++NOASSERTION1095500

CloudCompare

CloudCompare main repository

Language:C++NOASSERTION337200

Measur3D

A light and compact MERN application for the management of CityJSON city models

Language:JavaScriptApache-2.01600

Point-clouds-classification-and-integration-in-VR-environment

Ce projet est développé dans le cadre de mon travail de fin d'étude à l'université de Liège, unité de géomatique pour l'obtention de diplôme d'ingénieur en sciences géomatiques et ingénierie topographique à l'institut agronomique et vétérinaire Hassan 2. il consiste à la classification des nuages de points massifs pour l'ajout de l’information sémantique, et l’intégration dans un environnement de réalité virtuelle à l'aide de l'oculus Rift.

100