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We examine the task of point-level object segmentation in outdoor urban LIDAR scans. A key challenge in this area is the problem of missing points in the scans due to technical limitations of the LIDAR sensors. Our core contributions are demonstrating the benefit of reframing the segmentation task over the scan acquisition grid as opposed to considering only the acquired 3D point cloud and developing...
Unprecedented amounts of 3D data can be acquired in urban environments, but their use for scene understanding is challenging due to varying data resolution and variability of objects in the same class. An additional challenge is due to the nature of the point clouds themselves, since they lack detailed geometric or semantic information that would aid scene understanding. In this paper we present a...
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