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Addressing Diverging Training Costs using Local Restoration for Precise Bird's Eye View Map Construction
Our extensive experiments show that the TNN mechanism provides a plug-and-play memory-efficient pipeline, thereby enabling the effective estimation of real-sized (or precise) semantic labels for BEV map construction.
BroadBEV: Collaborative LiDAR-camera Fusion for Broad-sighted Bird's Eye View Map Construction
The method boosts the learning of depth estimation of the camera branch and induces accurate location of dense camera features in BEV space.
DeepLO: Geometry-Aware Deep LiDAR Odometry
We incorporate the Iterated Closest Point (ICP) algorithm into a deep-learning framework and show the reliability of the proposed pipeline.
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