English(EN) GRADE: Single-Frame Generative Radar Depth Estimation Under Visual Degradation

GRADE系统利用生成式AI改善低能见度下的雷达深度估计

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-11 04:00

研究人员开发了GRADE，一个用于从单帧雷达数据估计高保真度度量深度的新颖系统，尤其是在烟雾、雾和黑暗等具有挑战性的视觉条件下。GRADE利用预训练的生成式先验，特别是潜在扩散模型，并以从原始雷达频谱派生的粗略深度估计来条件化其去噪过程。当有相机线索可用时，像素空间适配器会将其纳入，从而使系统在能见度下降时也能接近雷达条件下的性能。在具有真实烟雾的各种室内环境中进行测试，GRADE表现强劲，在清晰和受烟雾影响的场景中均实现了低平均绝对误差（MAE），优于现有方法。 AI

影响增强了在传统视觉传感器失效的环境中的深度感知能力，可能改进机器人和自主系统。

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arXiv cs.CV TIER_1 English(EN) · Bin Zhao, Patrick Chiou, Nakul Garg · 2026-09-11 04:00

GRADE：视觉降级下的单帧生成雷达深度估计

arXiv:2609.10756v1 Announce Type: new Abstract: Dense 3D depth perception fails under smoke, fog, and darkness because optical sensors cannot penetrate airborne particulates. mmWave radar remains usable and measures range accurately under these conditions, but its small aperture …

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GRADE：视觉降级下的单帧生成雷达深度估计

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