| CPC G06V 20/58 (2022.01) [G06V 10/267 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 2201/08 (2022.01)] | 18 Claims |

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1. A method, comprising:
receiving, with at least one processor, a pseudo-image of a 3D image of an environment, wherein the 3D image is received from a 3D image sensor coupled to a vehicle, and wherein the pseudo-image comprises a grid of sections;
concurrently determining, with the at least one processor;
an object classification for a a plurality of sections of the pseudo-image using a first neural network, and
an instance portion classification for the plurality of sections of the pseudo-image using a second neural network;
combining, for each section of the plurality of sections, the object classification for the section and the instance portion classification for the section to form combined features for the section;
grouping a first section of the plurality of sections with a second section of the plurality of sections using the combined features of the first section and the combined features of the second section;
identifying a particular instance of an object in the environment using the grouped first section and second section; and
causing the vehicle to navigate based at least in part on the identified instances.
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