• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Generalizing Neural Radiance Fields for Robust 6D Pose Estimation of Unseen Appearances
 
  • Details
  • Full
Options
2025
Conference Paper
Title

Generalizing Neural Radiance Fields for Robust 6D Pose Estimation of Unseen Appearances

Abstract
Estimating the 6D pose of objects is a critical challenge for robotics and augmented reality applications. The problem is aggravated by the fact that critical attributes, such as an object’s texture and material, as well as the specific lighting conditions under which it must be identified, are often unknown. Neural Radiance Fields (NeRFs) and 3D Gaussian splatting (3DGS) are techniques that enable high-quality reconstruction of real-world scenes. By revising the scene fitting function, these representations can facilitate the estimation of an object’s pose within a given environment. However, a major complication is that the unique textures, materials, and lighting conditions are fixed within the scene, which can impair the accuracy of pose estimation. To address this, we adopt two alterations to the standard NeRF framework that enhance its ability to handle greatly varied object appearances such as material and texture. Our modified approaches are evaluated on the prevalent YCB-V object dataset, demonstrating their effectiveness. Our two proposed algorithms achieve mesh-free 6D Object Pose Estimation for objects with previously unseen appearances, requiring only a collection of input images to train the NeRF model.
Author(s)
Pöllabauer, Thomas  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Wirth, Tristan
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Weitz, Paul
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Knauthe, Volker
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Kuijper, Arjan  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Fellner, Dieter
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
Advances in Visual Computing. 19th International Symposium, ISVC 2024. Proceedings. Pt.I  
Project(s)
Non-Destructive Inspection Services for Digitally Enhanced Zero Waste Manufacturing  
Funder
European Commission  
Conference
International Symposium on Visual Computing 2024  
DOI
10.1007/978-3-031-77392-1_23
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Automotive Industry

  • Branche: Healthcare

  • Branche: Information Technology

  • Branche: Cultural and Creative Economy

  • Research Line: Computer graphics (CG)

  • Research Line: Computer vision (CV)

  • Research Line: Machine learning (ML)

  • LTA: Machine intelligence, algorithms, and data structures (incl. semantics)

  • LTA: Generation, capture, processing, and output of images and 3D models

  • 3D Computer vision

  • Machine learning

  • Pattern recognition

  • 3D Object localisation

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024