公开(公告)号：US20240296623A1

公开(公告)日：2024-09-05

申请号：US18169825

申请日：2023-02-15

Applicant: Nvidia Corporation

Inventor： Jiahui Huang ,  Francis Williams ,  Zan Gojcic ,  Matan Atzmon ,  Or Litany ,  Sanja Fidler

IPC: G06T17/20 ,  G06T15/08

CPC classification number: G06T17/20 ,  G06T15/08 ,  G06T2210/56

Abstract: Approaches presented herein provide for the reconstruction of implicit multi-dimensional shapes. In one embodiment, oriented point cloud data representative of an object can be obtained using a physical scanning process. The point cloud data can be provided as input to a trained density model that can infer density functions for various points. The points can be mapped to a voxel hierarchy, allowing density functions to be determined for those voxels at the various levels that are associated with at least one point of the input point cloud. Contribution weights can be determined for the various density functions for the sparse voxel hierarchy, and the weighted density functions combined to obtain a density field. The density field can be evaluated to generate a geometric mesh where points having a zero, or near-zero, value are determined to contribute to the surface of the object.

公开(公告)号：US20250131685A1

公开(公告)日：2025-04-24

申请号：US18674668

申请日：2024-05-24

Applicant: NVIDIA Corporation

Inventor： Sanja FIDLER ,  Matan Atzmon ,  Jiahui Huang ,  Or Litany ,  Francis Williams

IPC: G06V10/44 ,  G06V10/82

Abstract: In various examples, a technique for modeling equivariance in point neural networks includes generating, via execution of one or more layers included in a neural network, a set of features associated with a first partition prediction for a plurality of points included in a scene. The technique also includes applying, to the set of features, one or more transformations included in a frame associated with the plurality of points to generate a set of equivariant features. The technique further includes generating a second partition prediction for the plurality of points based at least on the set of equivariant features, and causing an object recognition result associated with the plurality of points to be generated based at least on the second partition prediction.