A Unified Framework for Multi-View Multi-Class Object Pose Estimation

ECCV 2018 Chi LiJin BaiGregory D. Hager

One core challenge in object pose estimation is to ensure accurate and robust performance for large numbers of diverse foreground objects amidst complex background clutter. In this work, we present a scalable framework for accurately inferring six Degree-of-Freedom (6-DoF) pose for a large number of object classes from single or multiple views... (read more)

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