公开(公告)号：US11380061B2

公开(公告)日：2022-07-05

申请号：US17177896

申请日：2021-02-17

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Ziyun Wang ,  Eric Anthony Mitchell ,  Ibrahim Volkan Isler ,  Daniel Dongyuel Lee

IPC: G06T17/20 ,  H04L67/10 ,  G06N3/04 ,  G06N3/08

Abstract: An apparatus for reconstructing a 3D object, includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain, using a first neural network, mapping function weights of a mapping function of a second neural network, based on an image feature vector corresponding to a 2D image of the 3D object, set the mapping function of the second neural network, using the obtained mapping function weights, and based on sampled points of a canonical sampling domain, obtain, using the second neural network of which the mapping function is set, 3D point coordinates and geodesic lifting coordinates of each of the sampled points in the 3D object corresponding to the 2D image, wherein the 3D point coordinates are first three dimensions of an embedding vector of a respective one of the sampled points, and the geodesic lifting coordinates are remaining dimensions of the embedding vector.

公开(公告)号：US20210390776A1

公开(公告)日：2021-12-16

申请号：US17177896

申请日：2021-02-17

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Ziyun Wang ,  Eric Anthony Mitchell ,  Ibrahim Volkan Isler ,  Daniel Dongyuel Lee

IPC: G06T17/20 ,  G06N3/08 ,  G06N3/04 ,  H04L29/08

Abstract: An apparatus for reconstructing a 3D object, includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain, using a first neural network, mapping function weights of a mapping function of a second neural network, based on an image feature vector corresponding to a 2D image of the 3D object, set the mapping function of the second neural network, using the obtained mapping function weights, and based on sampled points of a canonical sampling domain, obtain, using the second neural network of which the mapping function is set, 3D point coordinates and geodesic lifting coordinates of each of the sampled points in the 3D object corresponding to the 2D image, wherein the 3D point coordinates are first three dimensions of an embedding vector of a respective one of the sampled points, and the geodesic lifting coordinates are remaining dimensions of the embedding vector.