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A key technical challenge in performing 6D object pose estimation from RGB-D image is to fully leverage the two complementary data sources.
SOTA for 6D Pose Estimation using RGB on YCB-Video (Mean AUC metric )
We conduct extensive experiments on our YCB-Video dataset and the OccludedLINEMOD dataset to show that PoseCNN is highly robust to occlusions, can handle symmetric objects, and provide accurate pose estimation using only color images as input.
SOTA for 6D Pose Estimation using RGBD on YCB-Video (Mean ADD-S metric )
The approach was part of the MIT-Princeton Team system that took 3rd- and 4th- place in the stowing and picking tasks, respectively at APC 2016.
The hand's point cloud is pruned and robust global registration is performed to generate object pose hypotheses, which are clustered.