Memory efficient conversion between pointcloud and mesh data formats

Graduate Thesis 研究生毕业论文

A wrapper repo to control mitsuba2 to render point cloouds and meshes in a more programmingly way.

Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation) with added ROS integration

Example code to read uncompressed LAS and compressed LAZ files easily using LASlib

A set of examples on the various ways to compile python code, with benchmarking.

TLS processing pipeline creates for an ongoing microclimate investigation by the EDYSAN lab.

Command-line interface tool designed for photogrammetry tasks using Meshroom's AliceVision and CloudCompare

A curated list of awesome Point Cloud Processing algorithms

Package that can be used to merge multiple sensor_msgs/PointCloud2

Neste Jupyter Notebook ensino como manipular nuvens de pontos 3D com diversas bibliotecas do python. Diversos exemplos de visualização, pré-processamento, registro e alimentação de uma rede neural (MLP) com nuvens de pontos 3D são comentados e testados.

Bei der Vermessung eines physischen Raumes ist das Ergebnis eine Punktwolke. Diese Punktwolke beschreibt dann ausgewählte Punkte im Raum, zum Beispiel auf den Wänden und der Decke. Wenn diese Punkte in zwei seperaten Messungen gemessen werden, vielleicht sogar von unterschiedlichen Geräten, soll hinterher herausgefunden werden wie genau diese Pu…

Here you can find some commonly used algorithms in 3D image processing (3D Bildverarbeitung).

Bachelor's thesis project with the aim of creating a tool that can offer the possibility of evaluate the accuracy of classifications identified in high-density point clouds

A useful tool to cut a set of point cloud into two parts with a designed IoU (overlapping)

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.

Research notebooks on CV automation techniques

3ِD Change Detection In Point Cloud

The "Knowledge-based object Detection in Image and Point cloud" (KnowDIP) project aims at the conception of a framework for automatic object detection in unstructured and heterogeneous data. This framework uses a representation of human knowledge in order to improve the flexibility, accuracy, and efficiency of data processing.