3D object reconstruction with multi-view RGB-D images.

Education, research and development using the Simultaneous Localization and Mapping (SLAM) method.

Import a point cloud file and perform poisson 3D surface reconstruction algorithm, integrated with third-party libraries (e.g. open3d, pymeshlab...)

Course submission material for Lidar point cloud based 3D Detection using Yolo for Udacity Self Driving Nanodegree

Simple 3D-Scanner/PCD generator using Intel Realsense L515 camera and rotation matrices

🦾 🎭 An OpenCV based python application to add 3D mask to videos using Google mediapipe

TDAzureMerger: a Point-Cloud Merger for Azure Kinects.

Python module to query an fetch the 3D-ARD project

Type stubs for Open3D

3D Surface and Mesh Reconstruction from RGB Videos using COLMAP and Open3D

Stereo camera depth estimation with opencv and visualization in Open3D on jetson nano with CUDA support

open3d-visualise-point-cloud-in-bin-format

A modular, high-fidelity 3D inspection framework for detecting geometric deviations in engineered components through CAD-referenced scan analysis, precise point cloud registration, and spatial deviation mapping.

A Python-based photogrammetry pipeline for 3D reconstruction using COLMAP and Open3D. Features include feature extraction, matching, sparse/dense reconstruction, and texture mapping.

Udacity Self Driving Car Nanodegree: sensor fusion midterm proj

RealSense Point Cloud Visualizer in Open3D-Python

This project estimates tree crown volumes using 3D modeling and high-resolution LiDAR datasets (AHN4 and Kavel_10) in Nijmegen, Netherlands. The study focuses on tree detection, biophysical parameter estimation, and crown volume mapping, highlighting applications in urban green space management and ecosystem services. Tools: Python, LiDAR, GIS soft

Data Generation: Data is a spherical projection of the 3-D meshes.

A Python prototype that converts 2D photos or text prompts into 3D models (.ply) using depth estimation and surface reconstruction