PLARD:用于道路检测的渐进式LiDAR自适应-源码

Python

平板在PyTorch中实施的渐进式LiDAR自适应道路检测该存储库再现了PyTorch中PLARD 的结果。该代码主要基于。抽象的尽管基于视觉图像的道路检测技术发展Swift，但由于光照变化和图像模糊等问题，如何在视觉图像中可靠地识别道路区域仍然具有挑战性。为此，可以将LiDAR传感器数据并入以改进基于视觉图像的道路检测，因为LiDAR数据不易受到视觉噪声的影响。但是，将LiDAR信息引入基于视觉图像的道路检测中的主要困难是LiDAR数据及其提取的特征与视觉数据和视觉特征不会共享相同的空间。这样的空间间隙可能会限制LiDAR信息在道路检测中的优势。为了克服这个问题，我们引入了一种新颖的渐进式LiDAR自适应道路检测（PLARD）方法，以将LiDAR信息适应基于可视图像的道路检测并提高检测性能。在PLARD中，渐进式LiDAR适应包括两个后续模块：1）数据空间适应，通过

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