公开(公告)号：US20250061654A1

公开(公告)日：2025-02-20

申请号：US18806248

申请日：2024-08-15

Applicant: DASSAULT SYSTEMES

Inventor： Tom DURAND ,  Iheb BEN SALEM

IPC: G06T17/00 ,  G06T7/60 ,  G06V10/25

Abstract: A computer-implemented method for determining a machine-learning function configured for taking an input 3D scene and for outputting one or more camera viewpoints each for generating a respective 2D rendering of the 3D scene. The method includes obtaining a library having 3D scenes. The method includes, based on the library, forming a first dataset for training a first neural network configured for outputting a camera position and forming a second dataset for training a second neural network configured for outputting a camera orientation. The method includes training the first neural network based on the first dataset and training the second neural network based on the second dataset. Each camera viewpoint outputted by the machine-learning function includes a camera position and a camera orientation. Such a method forms an improved solution for outputting one or more camera viewpoints of a 3D scene.

公开(公告)号：US20240221176A1

公开(公告)日：2024-07-04

申请号：US18400517

申请日：2023-12-29

Applicant: DASSAULT SYSTEMES

Inventor： Paul JACOB ,  Tom DURAND ,  Ana MARCUSANU

IPC: G06T7/20

CPC classification number: G06T7/20 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A computer-implemented method for generating a training dataset. The training dataset includes training patterns each including a 3D point cloud of a respective travelable environment. The generating method includes, for each 3D point cloud, obtaining a 3D surface representation of the respective travelable environment, determining a traveling path inside the respective travelable environment, and, generating a virtual scan of the respective travelable environment along the traveling path, thereby obtaining the 3D point cloud. Such a method forms an improved solution for generating a training dataset of 3D point clouds.

公开(公告)号：US20230076988A1

公开(公告)日：2023-03-09

申请号：US17894498

申请日：2022-08-24

Applicant: DASSAULT SYSTEMES

Inventor： Tom DURAND ,  Ana MARCUSANU

IPC: G06F30/27 ,  G06F30/12 ,  G06F30/13 ,  G06Q10/06

Abstract: A computer-implemented method for automatically furnishing a 3D room based on user preferences including obtaining at least one spatial relations graph of a virtual 3D room and a set of user preferences, converting the set of user preferences into a set of target parameters, computing, for each spatial relations graph: a set of Key Performance Indicator values, and a KPI distance, automatically selecting at least one most promising spatial relations graph, instantiating the most promising spatial relations graph into the 3D room to be furnished, displaying the furnished virtual 3D room proposal to the user, receiving an update of the user preferences, and reiterating until a stopping criterion is fulfilled.

公开(公告)号：US20220335171A1

公开(公告)日：2022-10-20

申请号：US17658187

申请日：2022-04-06

Applicant: DASSAULT SYSTEMES

Inventor： Tom DURAND ,  Ana MARCUSANU ,  Aurélien LOUIS ,  Célia AEPLY ,  Julie FARRE

IPC: G06F30/12 ,  G06F30/13 ,  G06F30/17 ,  G06F30/25

Abstract: A computer-implemented method for automatically providing at least a template of a furnished virtual 3D room including 3D elements, including, for each furnished virtual 3D room: automatically extracting a spatial relations graph based on spatial relations between the 3D elements of the 3D room, said 3D elements including 3D architectural elements and 3D furnishing objects located in the furnished virtual 3D room, automatically extracting at least one zone from the 3D room based on the spatial relations graph, and extracting a set of constraints about a relative arrangement of said zone with respect to the room architecture or with respect to other zones of the 3D room, a zone being defined by a local spatial arrangement of at least one 3D furnishing object, and storing a template of the furnished virtual 3D room, said template including said zone and said set of constraints.

公开(公告)号：US20220189070A1

公开(公告)日：2022-06-16

申请号：US17553403

申请日：2021-12-16

Applicant: Dassault Systemes

Inventor： Asma REJEB SFAR ,  Tom DURAND ,  Ashad HOSENBOCUS

IPC: G06T9/00 ,  G06V10/74 ,  G06V10/82 ,  G06N3/08

Abstract: A computer-implemented method of machine-learning for learning a neural network that encodes a super-point of a 3D point cloud into a latent vector. The method including obtaining a dataset of super-points. Each super-point is a set of points of a 3D point cloud. The set of points represents at least a part of an object. The method further includes learning the neural network based on the dataset of super-points. The learning includes minimizing a loss. The loss penalizes a disparity between two super-points. This constitutes improved machine-learning for 3D object detection.

公开(公告)号：US20210192254A1

公开(公告)日：2021-06-24

申请号：US17124452

申请日：2020-12-16

Applicant: DASSAULT SYSTEMES

Inventor： Asma REJEB SFAR ,  Tom DURAND ,  Malika BOULKENAFED

IPC: G06K9/20 ,  G06T7/11 ,  G06N3/08

Abstract: A computer-implemented method of machine-learning including obtaining a dataset of 3D point clouds. Each 3D point cloud includes at least one object. Each 3D point cloud is equipped with a specification of one or more graphical user-interactions each representing a respective selection operation of a same object in the 3D point cloud. The method further includes teaching, based on the dataset, a neural network configured for segmenting an input 3D point cloud including an object. The segmenting is based on the input 3D point cloud and on a specification of one or more input graphical user-interactions each representing a respective selection operation of the object in the 3D point cloud.