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  4. EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation
 
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2025
Conference Paper
Title

EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation

Abstract
In industrial applications requiring real-time feedback, such as quality control and robotic manipulation, the demand for high-speed and accurate pose estimation remains critical. Despite advances improving speed and accuracy in pose estimation, finding a balance between computational efficiency and accuracy poses significant challenges in dynamic environments. Most current algorithms lack scalability in estimation time, especially for diverse datasets, and the state-of-the-art methods are often too slow. This study focuses on developing a fast and scalable set of pose estimators based on GDRNPP to meet or exceed current benchmarks in accuracy and robustness, particularly addressing the efficiency-accuracy trade-off essential in real-time scenarios. We propose the AMIS algorithm to tailor the utilized model according to an application-specific trade-off between inference time and accuracy. We further show the effectiveness of the AMIS-based model choice on four prominent benchmark datasets (LM-O, YCB-V, T-LESS, and ITODD).
Author(s)
Fang, Zixuan
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Pöllabauer, Thomas  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Wirth, Tristan
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Berkei, Sarah
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Knauthe, Volker
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Kuijper, Arjan  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
Image Analysis. 23rd Scandinavian Conference, SCIA 2025. Proceedings. Part II  
Conference
Scandinavian Conference on Image Analysis 2025  
DOI
10.1007/978-3-031-95918-9_14
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Information Technology

  • Research Line: Computer vision (CV)

  • Research Line: Modeling (MOD)

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

  • Object pose estimation

  • Machine learning

  • Efficiency

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