公开(公告)号：US11880913B2

公开(公告)日：2024-01-23

申请号：US17452568

申请日：2021-10-27

Applicant: Adobe Inc. ,  University of Massachusetts

Inventor： Aaron Hertzmann ,  Matthew Fisher ,  Difan Liu ,  Evangelos Kalogerakis

IPC: G06T11/00 ,  G06T11/20 ,  G06N3/045

CPC classification number: G06T11/001 ,  G06N3/045 ,  G06T11/203 ,  G06T2200/04

Abstract: Techniques for generating a stylized drawing of three-dimensional (3D) shapes using neural networks are disclosed. A processing device generates a set of vector curve paths from a viewpoint of a 3D shape; extracts, using a first neural network of a plurality of neural networks of a machine learning model, surface geometry features of the 3D shape based on geometric properties of surface points of the 3D shape; determines, using a second neural network of the plurality of neural networks of the machine learning model, a set of at least one predicted stroke attribute based on the surface geometry features and a predetermined drawing style; generates, based on the at least one predicted stroke attribute, a set of vector stroke paths corresponding to the set of vector curve paths; and outputs a two-dimensional (2D) stylized stroke drawing of the 3D shape based at least on the set of vector stroke paths.

公开(公告)号：US20240161355A1

公开(公告)日：2024-05-16

申请号：US18419287

申请日：2024-01-22

Applicant: Adobe Inc. ,  University of Massachusetts

Inventor： Aaron Hertzmann ,  Matthew Fisher ,  Difan Liu ,  Evangelos Kalogerakis

IPC: G06T11/00 ,  G06N3/045 ,  G06T11/20

CPC classification number: G06T11/001 ,  G06N3/045 ,  G06T11/203 ,  G06T2200/04

Abstract: Techniques for generating a stylized drawing of three-dimensional (3D) shapes using neural networks are disclosed. A processing device generates a set of vector curve paths from a viewpoint of a 3D shape; extracts, using a first neural network of a plurality of neural networks of a machine learning model, surface geometry features of the 3D shape based on geometric properties of surface points of the 3D shape; determines, using a second neural network of the plurality of neural networks of the machine learning model, a set of at least one predicted stroke attribute based on the surface geometry features and a predetermined drawing style; generates, based on the at least one predicted stroke attribute, a set of vector stroke paths corresponding to the set of vector curve paths; and outputs a two-dimensional (2D) stylized stroke drawing of the 3D shape based at least on the set of vector stroke paths.

公开(公告)号：US20250124212A1

公开(公告)日：2025-04-17

申请号：US18507847

申请日：2023-11-13

Applicant: Adobe Inc.

Inventor： Difan Liu ,  Matthew David Fisher ,  Michaël Yanis Gharbi ,  Oliver Wang ,  Alec Stefan Jacobson ,  Vikas Thamizharasan ,  Evangelos Kalogerakis

IPC: G06F40/109 ,  G06T11/20 ,  G06T11/40

Abstract: In implementation of techniques for vector font generation based on cascaded diffusion, a computing device implements a glyph generation system to receive a sample glyph in a target font and a target glyph identifier. The glyph generation system generates a rasterized glyph in the target font using a raster diffusion model based on the sample glyph and the target glyph identifier, the rasterized glyph having a first level of resolution. The glyph generation system then generates a vector glyph using a vector diffusion model by vectorizing the rasterized glyph, the vector glyph having a second level of resolution different than the first level of resolution. The glyph generation system then displays the vector glyph in a user interface.

公开(公告)号：US11875442B1

公开(公告)日：2024-01-16

申请号：US17829120

申请日：2022-05-31

Applicant: Adobe Inc. ,  University of Massachusetts

Inventor： Matthew David Fisher ,  Zhan Xu ,  Yang Zhou ,  Deepali Aneja ,  Evangelos Kalogerakis

IPC: G06T13/80 ,  G06V10/762 ,  G06T13/40 ,  G06V10/774 ,  G06T7/246 ,  G06V10/77

CPC classification number: G06T13/80 ,  G06T7/251 ,  G06T13/40 ,  G06V10/762 ,  G06V10/7715 ,  G06V10/7747

Abstract: Embodiments are disclosed for articulated part extraction using images of animated characters from sprite sheets by a digital design system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input including a plurality of images depicting an animated character in different poses. The disclosed systems and methods further comprise, for each pair of images in the plurality of images, determining, by a first machine learning model, pixel correspondences between pixels of the pair of images, and determining, by a second machine learning model, pixel clusters representing the animated character, each pixel cluster corresponding to a different structural segment of the animated character. The disclosed systems and methods further comprise selecting a subset of clusters that reconstructs the different poses of the animated character. The disclosed systems and methods further comprise creating a rigged animated character based on the selected subset of clusters.

公开(公告)号：US20230360376A1

公开(公告)日：2023-11-09

申请号：US17744995

申请日：2022-05-16

Applicant: Adobe Inc.

Inventor： Tobias Hinz ,  Taesung Park ,  Richard Zhang ,  Matthew David Fisher ,  Difan Liu ,  Evangelos Kalogerakis

IPC: G06V10/774 ,  G06V10/22 ,  G06T3/40

CPC classification number: G06V10/7753 ,  G06V10/235 ,  G06T3/4046

Abstract: Semantic fill techniques are described that support generating fill and editing images from semantic inputs. A user input, for example, is received by a semantic fill system that indicates a selection of a first region of a digital image and a corresponding semantic label. The user input is utilized by the semantic fill system to generate a guidance attention map of the digital image. The semantic fill system leverages the guidance attention map to generate a sparse attention map of a second region of the digital image. A semantic fill of pixels is generated for the first region based on the semantic label and the sparse attention map. The edited digital image is displayed in a user interface.

公开(公告)号：US20230109732A1

公开(公告)日：2023-04-13

申请号：US17452568

申请日：2021-10-27

Applicant: Adobe Inc. ,  University of Massachusetts

Inventor： Aaron Hertzmann ,  Matthew Fisher ,  Difan Liu ,  Evangelos Kalogerakis

IPC: G06T11/00 ,  G06T11/20 ,  G06N3/04

Abstract: Techniques for generating a stylized drawing of three-dimensional (3D) shapes using neural networks are disclosed. A processing device generates a set of vector curve paths from a viewpoint of a 3D shape; extracts, using a first neural network of a plurality of neural networks of a machine learning model, surface geometry features of the 3D shape based on geometric properties of surface points of the 3D shape; determines, using a second neural network of the plurality of neural networks of the machine learning model, a set of at least one predicted stroke attribute based on the surface geometry features and a predetermined drawing style; generates, based on the at least one predicted stroke attribute, a set of vector stroke paths corresponding to the set of vector curve paths; and outputs a two-dimensional (2D) stylized stroke drawing of the 3D shape based at least on the set of vector stroke paths.