Detections: 3PT
(run for all available views)

Single-view: FoundPose + FeatRef + Megapose
(run for all available views)

Multi-view: AlignPose

The presented results were obtained by the AlignPose [1] multi-view pipeline. Each view is first processed independently using 2D detections from 3PT-Detection and SAM2 [2] segmentations. Initial pose estimates are obtained for each view with single-view method FoundPose [3] and refined with FoundPose featuremetric refinement and MegaPose [4] refinement. Multi-view consistent poses are produced with AlignPose pipeline that aggregates all single-view candidates with Non Maximal Suppression and refines them with multi-view feature-metric refinement.

[1] Anonymous: AlignPose: Generalizable 6D Pose Estimation via Multi-view Feature-metric Alignment
[2] Ravi, Nikhila, et al. "SAM 2: Segment Anything in Images and Videos." The Thirteenth International Conference on Learning Representations, 2025.
[3] Örnek, Evin Pınar, et al. "FoundPose: Unseen Object Pose Estimation with Foundation Features." European Conference on Computer Vision. Cham: Springer Nature Switzerland, 2024.
[4] Labbé, Yann, et al. "MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare." Conference on Robot Learning, 2022.