PointVoteNet: Accurate Object Detection and 6 DoF Pose Estimation in Point Clouds

Understand

We present a learning-based method for 6 DoF pose estimation of rigid objects in point cloud data.

• Many recent learning-based approaches use primarily RGB information for detecting objects, in some cases with an added refinement step using depth data.
• Our method consumes unordered point sets with/without RGB information, from initial detection to the final transformation estimation stage.
• This allows us to achieve accurate pose estimates, in some cases surpassing state of the art methods trained on the same data.