CPC G01S 7/4802 (2013.01) [G01S 7/481 (2013.01); G01S 17/894 (2020.01); G01S 17/931 (2020.01); G06V 10/764 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/58 (2022.01); G01S 7/28 (2013.01)] | 19 Claims |
1. A method comprising:
applying, to a deep neural network (DNN), first data corresponding to a range image, the range image being generated using sensor data from a LiDAR point cloud;
computing, using the DNN and for the range image corresponding to the first data, one or more segmentation masks representing one or more portions of the range image that correspond to one or more objects;
computing, using the DNN and for the range image corresponding to the first data, one or more locations within the range image of one or more bounding shape proposals corresponding to the one or more objects;
correlating the one or more bounding shape proposals for the range image with the one or more segmentation masks for the range image;
based at least on the correlating, generating one or more projected bounding shape proposals by projecting the one or more locations of the one or more bounding shape proposals within the range image to one or more corresponding locations in the LiDAR point cloud; and
performing one or more operations using a machine based at least on the one or more projected bounding shape proposals.
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