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BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation. (arXiv:2205.13542v2 [cs.CV] UPDATED)
Web: http://arxiv.org/abs/2205.13542
June 17, 2022, 1:13 a.m. | Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela Rus, Song Han
cs.CV updates on arXiv.org arxiv.org
Multi-sensor fusion is essential for an accurate and reliable autonomous
driving system. Recent approaches are based on point-level fusion: augmenting
the LiDAR point cloud with camera features. However, the camera-to-LiDAR
projection throws away the semantic density of camera features, hindering the
effectiveness of such methods, especially for semantic-oriented tasks (such as
3D scene segmentation). In this paper, we break this deeply-rooted convention
with BEVFusion, an efficient and generic multi-task multi-sensor fusion
framework. It unifies multi-modal features in the shared bird's-eye …
More from arxiv.org / cs.CV updates on arXiv.org
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