Fast Uncertainty Quantification for Deep Object Pose Estimation
Guanya Shi Yifeng Zhu Jonathan Tremblay Stan Birchfield Fabio Ramos Animashree Anandkumar Yuke Zhu Guanya Shi Yifeng Zhu Jonathan Tremblay Stan Birchfield Fabio Ramos Animashree Anandkumar Yuke Zhu
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, efficient, and plug-and-play UQ method for 6-DoF object pose esti...