Point cloud registration pipeline for robot localization and 3D perception
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Updated
May 28, 2024 - C++
Point cloud registration pipeline for robot localization and 3D perception
Point cloud map evaluation library for the FusionPortable dataset. Metrics include Mean Map Entropy (MME), RMSE, Accuracy(mean error), Precision(standard deviation), completeness(overlap ratio), chamfer distance and F1-score at all levels of 1/2/5/10/20cm.
🌟A curated list of DUSt3R-related papers and resources, tracking recent advancements using this geometric foundation model.
MVP Benchmark for Multi-View Partial Point Cloud Completion and Registration
Generalizing Neural Human Fitting to Unseen Poses With Articulated SE(3) Equivariance (ICCV2023)
[TITS] reliable dense matching based point cloud registration for autonomous driving
Linewise Non-Rigid Point Cloud Registration (C++)
[ICCV 2021] CPD with Local Surface Geometry (LSG-CPD)
Object recognition and 6 DoF pose estimation.
《IEEE TNNLS》RORNet: Partial-to-Partial Registration Network With Reliable Overlapping Representations
《IEEE TCSVT》INENet: Inliers Estimation Network with Similarity Learning for Partial Overlapping Registration
Source code of generalized shuffled linear regression
6 DoF pointcloud registration
LeManchot-Points is a system for fusion of multi-modal data captured by our data acquisition system
This repository contains sensor fusion between a lidar and camera, semantic segmentation on point clouds and ICP registration of multiple point clouds.
Pointcloud Registration Algorithm with noise and different scale management
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.
Repo containing my final project for the 3D Augmented Reality course at the University of Padova for the school year 22/23
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