公开(公告)号：US20250014186A1

公开(公告)日：2025-01-09

申请号：US18397921

申请日：2023-12-27

Applicant: NVIDIA Corporation

Inventor： Ke CHEN ,  Nikolai SMOLYANSKIY ,  Alexey KAMENEV ,  Ryan OLDJA ,  Tilman WEKEL ,  David NISTER ,  Joachim PEHSERL ,  Ibrahim EDEN ,  Sangmin OH ,  Ruchi BHARGAVA

IPC: G06T7/11 ,  G05D1/81 ,  G06F18/22 ,  G06F18/23 ,  G06T5/50 ,  G06T7/10 ,  G06V10/44 ,  G06V10/82 ,  G06V20/56 ,  G06V20/58

Abstract: A deep neural network(s) (DNN) may be used to perform panoptic segmentation by performing pixel-level class and instance segmentation of a scene using a single pass of the DNN. Generally, one or more images and/or other sensor data may be stitched together, stacked, and/or combined, and fed into a DNN that includes a common trunk and several heads that predict different outputs. The DNN may include a class confidence head that predicts a confidence map representing pixels that belong to particular classes, an instance regression head that predicts object instance data for detected objects, an instance clustering head that predicts a confidence map of pixels that belong to particular instances, and/or a depth head that predicts range values. These outputs may be decoded to identify bounding shapes, class labels, instance labels, and/or range values for detected objects, and used to enable safe path planning and control of an autonomous vehicle.