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New CrowdOcc framework enhances robot scene completion in crowded indoor spaces

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced CrowdOcc, a new framework and dataset designed to improve monocular semantic scene completion for quadruped robots operating in crowded indoor environments. The system addresses challenges posed by human-scene occlusions and incomplete occupancy predictions by integrating Normal Guided Scene Geometry Fusion (NGSGF) and Human-Centric Sparse Interaction (HCSI). This approach leverages surface-normal cues for robust geometry estimation and selectively models human-scene relationships in 3D, achieving state-of-the-art performance on its own test set. AI

IMPACT Enhances robot navigation and scene understanding in complex, human-populated indoor settings.

RANK_REASON The cluster contains a research paper detailing a new framework and dataset for a specific computer vision task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New CrowdOcc framework enhances robot scene completion in crowded indoor spaces

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The cluster contains a research paper detailing a new framework and dataset for a specific computer vision task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Feiyang Chen, Jincheng Hu, Yiduo Chen, Jihao Li, Yue Liang, Bingzhao Gao, Yanjun Huang, Yuanjian Zhang ·

    CrowdOcc: Monocular Semantic Scene Completion for Quadruped Robots in Crowded Indoor Environments

    arXiv:2610.03031v1 Announce Type: new Abstract: Monocular semantic scene completion (SSC) for quadruped robots remains underexplored in real crowded indoor environments, where human-scene occlusion disrupts static geometry and human occupancy predictions are often incomplete or s…

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