FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains

Authors

  • Di Jia Liaoning Technical University
  • Qian Wang Liaoning Technical University
  • Jun Cao Intel Corporation
  • Peng Cai Liaoning Technical University
  • Zhiyang Jin Liaoning Technical University

DOI:

https://doi.org/10.1609/aaai.v37i13.27077

Keywords:

6D Pose Tracking, Fast Convergence, Synthetic Data-driven

Abstract

In this work, we propose a fast convergence track net, or FC-TrackNet, based on a synthetic data-driven approach to maintaining long-term 6D pose tracking. Comparison experiments are performed on two different datasets, The results demonstrate that our approach can achieve a consistent tracking frequency of 90.9 Hz as well as higher accuracy than the state-of-the art approaches.

Downloads

Published

2023-09-06

How to Cite

Jia, D., Wang, Q., Cao, J., Cai, P., & Jin, Z. (2023). FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16455-16457. https://doi.org/10.1609/aaai.v37i13.27077