Fast Uncertainty Quantification for Deep Object Pose Estimation

Guanya Shi
Guanya Shi
Yifeng Zhu
Yifeng Zhu
Fabio Ramos
Fabio Ramos
Cited by: 0|Bibtex|Views8
Other Links: arxiv.org

Abstract:

Deep learning-based object pose estimators are often unreliable and overconfident especially when the input image is outside the training domain, for instance, with sim2real transfer. Efficient and robust uncertainty quantification (UQ) in pose estimators is critically needed in many robotic tasks. In this work, we propose a simple, eff...More

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