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English(EN) SurroundNEXO: Ego-Centric Metric Bridging for Spatially Consistent Geometry in Autonomous Driving

SurroundNEXO框架增强了自动驾驶的度量深度预测

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出SurroundNEXO，一个旨在改进自动驾驶系统度量深度预测的新型框架。该方法利用以自我为中心的几何和稀疏LiDAR测量作为尺度传播的锚点，解决了摄像头之间视觉重叠有限的挑战。SurroundNEXO在NuScenes、Waymo和DDAD等基准测试中，在减少单视图误差、增强跨视图一致性和提高度量重建质量方面取得了显著改进。 AI

影响 提高了自动驾驶系统在3D理解中的空间一致性和准确性。

排序理由 该集群包含一篇详细介绍自动驾驶新框架的学术论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

SurroundNEXO框架增强了自动驾驶的度量深度预测

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该集群包含一篇详细介绍自动驾驶新框架的学术论文。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Shuai Yuan, Runxi Tang, Yuzhou Ji, Fudong Ge, Hanshi Wang, Yifei Wang, Xianming Zeng, Jianyun Xu, Xingliang Liu, Yanfeng Wang, Zhipeng Zhang ·

    SurroundNEXO：用于自动驾驶中空间一致几何的以自我为中心的度量桥接

    arXiv:2606.16960v1 Announce Type: new Abstract: Modern autonomous driving depends on accurate metric 3D understanding for perception, reconstruction, and planning, which in turn requires reliable multi-camera depth prediction. However, the outward-facing nature of vehicle-mounted…

  2. arXiv cs.CV TIER_1 English(EN) · Zhipeng Zhang ·

    SurroundNEXO：用于自动驾驶中空间一致几何的以自我为中心的度量桥接

    Modern autonomous driving depends on accurate metric 3D understanding for perception, reconstruction, and planning, which in turn requires reliable multi-camera depth prediction. However, the outward-facing nature of vehicle-mounted surround-view camera rigs inherently limits vis…

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