Deutsche Nationalbibliothek
metadata only
GeoHash3D: Robust and Efficient 6-DoF Pose Estimation from 3D Marker Sets / Lijiu Wang, Kailas Mahalinga Upadhyaya, Oguz Kedilioglu, Michael Hofmann, Weimin Gan, Nico Hempel, Peter Mayr, Sebastian Reitelshöfer, Jörg Franke ; Herausgeber: Shahram Payandeh
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Prior-free relative 6D pose estimation of multiple object instances#986568
- RIDE: Relocalization-Informed Depth Estimation with 3D Gaussian Splatting#998639
- Back to the Feature: Zero-Shot 6DoF Pose Estimation via Dense Local Features#974820
- LBDU-VIO: Learned Bias Dynamics and Uncertainty for Visual-Inertial Odometry with Unreliable Vision#1144092
- MDE-VIO: Enhancing Visual-Inertial Odometry Using Learned Depth Priors#1077863
Record · ID 675548
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive