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New uScenes dataset aids underwater robot perception with sonar and RGB data

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Researchers have introduced uScenes, a new dataset designed to improve the perception capabilities of autonomous underwater robots. This multimodal dataset synchronizes 3D multibeam sonar point clouds with RGB imagery, addressing the limitations of optical cameras in poor underwater conditions and the elevation ambiguity of traditional 2D sonar. uScenes comprises 110 scenes and over 95,000 observations, totaling nearly 278 minutes of data, and aims to facilitate advancements in underwater sensor fusion, cross-modal representation learning, and 3D scene understanding. AI

IMPACT Enables improved sensor fusion and 3D scene understanding for autonomous underwater robots.

RANK_REASON The item describes a new dataset published on arXiv for computer vision research. [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 uScenes dataset aids underwater robot perception with sonar and RGB data

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The item describes a new dataset published on arXiv for computer vision research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Trung Tien Dong, Zhenqi Wu, Aditya Penumarti, Zi-Hao Zhang, Micaiah Bartlett, Jane Shin, Xiaomin Lin ·

    uScenes: A Multimodal RGB and 3D Sonar Dataset for Underwater Robot Perception

    arXiv:2608.27795v1 Announce Type: new Abstract: Robust perception is essential for the deployment of autonomous underwater robots. However, optical cameras become unreliable under poor illumination and backscatter. Forward looking (2D) acoustic sensors remain effective under thes…

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