公开(公告)号：US20220165030A1

公开(公告)日：2022-05-26

申请号：US17590702

申请日：2022-02-01

Applicant: Adobe Inc. ,  Institut Mines Telecom

Inventor： Thibaud Lambert ,  Tamy Boubekeur ,  Anthony Salvi

IPC: G06T17/20 ,  G06T3/40 ,  G06T11/00 ,  G06T5/00

Abstract: The disclosure describes one or more embodiments of systems, methods, and non-transitory computer-readable media that utilize a sharpness map that includes information on how to filter a displacement map on a per-texel basis to preserve sharp features while sampling a displacement map. For instance, the disclosed systems utilize a sharpness map that encodes combinable patterns to represent discontinuities of features within a displacement map. In some embodiments, the disclosed systems generate a sharpness map having texels encoded with discontinuity configurations that are referenced to control filtering (e.g., via interpolation) of a displacement map such that sharp features within the displacement map are not lost (due to smoothing during interpolation). For example, the disclosed systems filter feature values of a displacement map using discontinuities identified within a sharpness map to interpolate when the feature value(s) and a sampling point are identified as being on the same side of a discontinuity.

公开(公告)号：US11037341B1

公开(公告)日：2021-06-15

申请号：US16744105

申请日：2020-01-15

Applicant: Adobe Inc.

Inventor： Giorgio Gori ,  Tamy Boubekeur ,  Radomir Mech ,  Nathan Aaron Carr ,  Matheus Abrantes Gadelha ,  Duygu Ceylan Aksit

IPC: G06T11/20 ,  G06N20/00 ,  G06N7/00 ,  G06T9/00

Abstract: Generative shape creation and editing is leveraged in a digital medium environment. An object editor system represents a set of training shapes as sets of visual elements known as “handles,” and converts sets of handles into signed distance field (SDF) representations. A handle processor model is then trained using the SDF representations to enable the handle processor model to generate new shapes that reflect salient visual features of the training shapes. The trained handle processor model, for instance, generates new sets of handles based on salient visual features learned from the training handle set. Thus, utilizing the described techniques, accurate characterizations of a set of shapes can be learned and used to generate new shapes. Further, generated shapes can be edited and transformed in different ways.