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Cascaded Cross-Modality Fusion Network for 3D Object Detection
We focus on exploring the LIDAR-RGB fusion-based 3D object detection in this paper. This task is still challenging in two aspects: (1) the difference of data formats and sensor positions contributes to the misalignment of reasoning between the semantic features of images and the geometric features of point clouds. (2) The optimization of traditional IoU is not equal to the regression loss of bounding boxes, resulting in biased back-propagation for non-overlapping cases. In this work, we proposedoi:10.3390/s20247243 pmid:33348795 fatcat:735bmb2kjng7tf4rubxt2jarcq