Global Hypothesis Generation for 6D Object Pose Estimation

CVPR 2017 Frank MichelAlexander KirillovEric BrachmannAlexander KrullStefan GumholdBogdan SavchynskyyCarsten Rother

This paper addresses the task of estimating the 6D pose of a known 3D object from a single RGB-D image. Most modern approaches solve this task in three steps: i) Compute local features; ii) Generate a pool of pose-hypotheses; iii) Select and refine a pose from the pool... (read more)

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