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Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)

Tsu-Ching Hsiao · Hao-Wei Chen · Hsuan-Kung Yang · Chun-Yi Lee

Arch 4A-E Poster #18
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Wed 19 Jun 10:30 a.m. PDT — noon PDT

Abstract: Addressing pose ambiguity in 6D object pose estimation from single RGB images presents a significant challenge, particularly due to object symmetries or occlusions. In response, we introduce a novel score-based diffusion method applied to the $SE(3)$ group, marking the first application of diffusion models to $SE(3)$ within the image domain, specifically tailored for pose estimation tasks. Extensive evaluations demonstrate the method's efficacy in handling pose ambiguity, mitigating perspective-induced ambiguity, and showcasing the robustness of our surrogate Stein score formulation on $SE(3)$. This formulation not only improves the convergence of denoising process but also enhances computational efficiency. Thus, we pioneer a promising strategy for 6D object pose estimation.

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