公开(公告)号：US20240428514A1

公开(公告)日：2024-12-26

申请号：US18415454

申请日：2024-01-17

Applicant: NVIDIA Corporation

Inventor： Kang WANG ,  Yue WU ,  Minwoo PARK ,  Gang PAN

IPC: G06T17/05 ,  B60W30/09 ,  B60W30/14 ,  B60W40/06 ,  B60W50/06 ,  B60W60/00 ,  G06F18/214 ,  G06V20/05 ,  G06V20/58

Abstract: In various examples, to support training a deep neural network (DNN) to predict a dense representation of a 3D surface structure of interest, a training dataset is generated using a parametric mathematical modeling. A variety of synthetic 3D road surfaces may be generated by modeling a 3D road surface using varied parameters to simulate changes in road direction and lateral surface slope. In an example embodiment, a synthetic 3D road surface may be created by modeling a longitudinal 3D curve and expanding the longitudinal 3D curve to a 3D surface, and the resulting synthetic 3D surface may be sampled to form a synthetic ground truth projection image (e.g., a 2D height map). To generate corresponding input training data, a known pattern that represents which pixels may remain unobserved during 3D structure estimation may be generated and applied to a ground truth projection image to simulate a corresponding sparse projection image.