US 12,236,517 B2
Techniques for multi-view neural object modeling
Derek Edward Bradley, Zurich (CH); Prashanth Chandran, Zurich (CH); Paulo Fabiano Urnau Gotardo, Zurich (CH); Daoye Wang, Zurich (CH); and Gaspard Zoss, Zurich (CH)
Assigned to Disney Enterprises, INC., Burbank, CA (US); and ETH Zürich (Eidgenössische Technische Hochschule Zürich), Zurich (CH)
Filed by DISNEY ENTERPRISES, INC., Burbank, CA (US); and ETH Zürich (Eidgenössische Technische Hochschule Zürich), Zürich (CH)
Filed on Nov. 8, 2022, as Appl. No. 17/983,246.
Claims priority of provisional application 63/280,101, filed on Nov. 16, 2021.
Prior Publication US 2023/0154101 A1, May 18, 2023
Int. Cl. G06T 15/06 (2011.01); G06T 7/62 (2017.01); G06T 15/04 (2011.01)
CPC G06T 15/06 (2013.01) [G06T 7/62 (2017.01); G06T 15/04 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for rendering an image of an object, the method comprising:
tracing a ray through a pixel into a virtual scene;
sampling one or more positions along the ray;
applying a machine learning model to the one or more positions and an identifier (ID) code associated with an object to determine, for each position included in the one or more positions, a density, a diffuse color, and a specular color, wherein the ID code is used to determine a geometric deformation from a canonical object geometry, wherein the geometric deformation is associated with the object; and
computing a color of a pixel based on the density, the diffuse color, and the specular color corresponding to each position included in the one or more positions.