In this submission, CNOS_SAM [A] detections are used as input to the MegaPose pose estimation method [B].

For each detection, we run the MegaPose coarse network and refine the 1-best coarse estimate with 5 refiner iterations. Anti-aliasing in panda3d renderer is deactivated.

The following improvement has been made over the original MegaPose paper [B]: - The orientation of the coarse hypotheses are obtained my discretizing SO(3) in 576 values using [C].

[A] Nguyen et al.: CNOS: A Strong Baseline for CAD-based Novel Object Segmentation, arXiv 2023 [B] Labbé et al.: MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare, CoRL 2022 [C] Yershova et al.: Generating Uniform Incremental Grids on SO(3) Using the Hopf Fibration, IJRR 2009, reference implementation: http://lavalle.pl/software/so3/so3.html