Invention Grant
- Patent Title: 3D surface reconstruction with point cloud densification using deep neural networks for autonomous systems and applications
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Application No.: US17452747Application Date: 2021-10-28
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Publication No.: US12172667B2Publication Date: 2024-12-24
- Inventor: Kang Wang , Yue Wu , Minwoo Park , Gang Pan
- Applicant: NVIDIA Corporation
- Applicant Address: US CA Santa Clara
- Assignee: NVIDIA Corporation
- Current Assignee: NVIDIA Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Freestone Intellectual Property Law PLLC
- Main IPC: B60W60/00
- IPC: B60W60/00 ; B60W40/09 ; G06N3/02

Abstract:
In various examples, a 3D surface structure such as the 3D surface structure of a road (3D road surface) may be observed and estimated to generate a 3D point cloud or other representation of the 3D surface structure. Since the estimated representation may be sparse, a deep neural network (DNN) may be used to predict values for a dense representation of the 3D surface structure from the sparse representation. For example, a sparse 3D point cloud may be projected to form a sparse projection image (e.g., a sparse 2D height map), which may be fed into the DNN to predict a dense projection image (e.g., a dense 2D height map). The predicted dense representation of the 3D surface structure may be provided to an autonomous vehicle drive stack to enable safe and comfortable planning and control of the autonomous vehicle.
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