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In this paper, we propose a probabilistic approach to generate abstract scene graphs from uncertain 6D pose estimates. We focus on generating a semantic understanding of the perceived scenes that well explains the composition of the scene and the inter-object relations. The proposed system is realized by our knowledge-supervised MCMC sampling technique. We explicitly make use of task-specific context...
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