GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objects

Understand

Despite the progress of learning-based methods for 6D object pose estimation, the trade-off between accuracy and scalability for novel objects still exists.

• Specifically, previous methods for novel objects do not make good use of the target object's 3D shape information since they focus on generalization by processing the shape indirectly, making them less effective.
• We present GenFlow, an approach that enables both accuracy and generalization to novel objects with the guidance of the target object's shape.
• Our method predicts optical flow between the rendered image and the observed image and refines the 6D pose iteratively.