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English(EN) MIRAGE: Metric Inference and Reliability-Aware Gaussian Estimation from Feed-Forward Vision

MIRAGE系统通过融合视觉和激光雷达惯性数据增强3D重建

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了MIRAGE，一个集成前馈3D视觉与激光雷达惯性估计以提高3D重建质量的新颖系统。MIRAGE将视觉几何锚定到来自激光雷达-IMU数据的精确度量运动，同时根据对应支持和跨模态一致性来调节姿态校正。这种方法能够实现精确的度量姿态估计和高保真高斯重建，在Oxford Spires和M2DGR等基准测试中优于COLMAP等传统方法。该团队还创建了一个新的多模态数据集，用于评估室内长视线场景中的单目大规模重建方法。 AI

影响 通过整合视觉和传感器数据，提高了3D重建的准确性和保真度，可能改进机器人和自主系统中的应用。

排序理由 该项目是一篇关于3D重建新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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MIRAGE系统通过融合视觉和激光雷达惯性数据增强3D重建

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该项目是一篇关于3D重建新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xinzhe Wang, Changjian Jiang, Kaiwen Song, Xudong Li, Kerui Ren, Ran Yi, Lizhuang Ma, Chunhua Shen, Linning Xu, Tao Lu, Mulin Yu ·

    MIRAGE：前馈视觉中的度量推理与可靠性感知高斯估计

    arXiv:2610.12568v1 Announce Type: new Abstract: Feed-forward 3D priors enable high-quality reconstruction from image streams but often lack reliable metric scale and suffer from long-term trajectory drift. In contrast, LiDAR--inertial estimation provides metrically accurate motio…

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