公开(公告)号：US11875446B2

公开(公告)日：2024-01-16

申请号：US17662287

申请日：2022-05-06

Applicant: ADOBE INC.

Inventor： Paul Augusto Guerrero ,  Milos Hasan ,  Kalyan K. Sunkavalli ,  Radomir Mech ,  Tamy Boubekeur ,  Niloy Jyoti Mitra

IPC: G06T15/04 ,  G06T17/00 ,  G06V10/776 ,  G06V10/426 ,  G06V10/774 ,  G06V10/44

CPC classification number: G06T15/04 ,  G06T17/00 ,  G06V10/426 ,  G06V10/44 ,  G06V10/776 ,  G06V10/7747

Abstract: Aspects of a system and method for procedural media generation include generating a sequence of operator types using a node generation network; generating a sequence of operator parameters for each operator type of the sequence of operator types using a parameter generation network; generating a sequence of directed edges based on the sequence of operator types using an edge generation network; combining the sequence of operator types, the sequence of operator parameters, and the sequence of directed edges to obtain a procedural media generator, wherein each node of the procedural media generator comprises an operator that includes an operator type from the sequence of operator types, a corresponding sequence of operator parameters, and an input connection or an output connection from the sequence of directed edges that connects the node to another node of the procedural media generator; and generating a media asset using the procedural media generator.

公开(公告)号：US20250139883A1

公开(公告)日：2025-05-01

申请号：US18499673

申请日：2023-11-01

Applicant: ADOBE INC.

Inventor： Milos Hasan ,  Iliyan Georgiev ,  Sai Bi ,  Julien Philip ,  Kalyan K. Sunkavalli ,  Xin Sun ,  Fujun Luan ,  Kevin James Blackburn-Matzen ,  Zexiang Xu ,  Kai Zhang

IPC: G06T17/00 ,  G06T7/90 ,  H04N13/279

Abstract: Embodiments are configured to render 3D models using an importance sampling method. First, embodiments obtain a 3D model including a plurality of density values corresponding to a plurality of locations in a 3D space, respectively. Embodiments then sample the color information from within a random subset of the plurality of locations using a probability distribution based on the plurality of density values. Embodiments have a higher probability to sample each location within the random subset of locations if the location has a higher density probability. Embodiments then an image depicting a view of the 3D model based on the sampling within the random subset of the plurality of locations.

公开(公告)号：US11887241B2

公开(公告)日：2024-01-30

申请号：US17559867

申请日：2021-12-22

Applicant: Adobe Inc.

Inventor： Zexiang Xu ,  Yannick Hold-Geoffroy ,  Milos Hasan ,  Kalyan Sunkavalli ,  Fanbo Xiang

IPC: G06T15/04 ,  G06T15/20 ,  G06N3/08 ,  G06T19/20 ,  G06N3/045

CPC classification number: G06T15/04 ,  G06N3/045 ,  G06N3/08 ,  G06T15/20 ,  G06T19/20

Abstract: Embodiments are disclosed for neural texture mapping. In some embodiments, a method of neural texture mapping includes obtaining a plurality of images of an object, determining volumetric representation of a scene of the object using a first neural network, mapping 3D points of the scene to a 2D texture space using a second neural network, and determining radiance values for each 2D point in the 2D texture space from a plurality of viewpoints using a second neural network to generate a 3D appearance representation of the object.

公开(公告)号：US20230360310A1

公开(公告)日：2023-11-09

申请号：US17662287

申请日：2022-05-06

Applicant: ADOBE INC.

Inventor： Paul Augusto Guerrero ,  Milos Hasan ,  Kalyan K. Sunkavalli ,  Radomir Mech ,  Tamy Boubekeur ,  Niloy Jyoti Mitra

IPC: G06T15/04 ,  G06T17/00 ,  G06V10/44 ,  G06V10/426 ,  G06V10/774 ,  G06V10/776

CPC classification number: G06T15/04 ,  G06T17/00 ,  G06V10/44 ,  G06V10/426 ,  G06V10/7747 ,  G06V10/776

Abstract: Aspects of a system and method for procedural media generation include generating a sequence of operator types using a node generation network; generating a sequence of operator parameters for each operator type of the sequence of operator types using a parameter generation network; generating a sequence of directed edges based on the sequence of operator types using an edge generation network; combining the sequence of operator types, the sequence of operator parameters, and the sequence of directed edges to obtain a procedural media generator, wherein each node of the procedural media generator comprises an operator that includes an operator type from the sequence of operator types, a corresponding sequence of operator parameters, and an input connection or an output connection from the sequence of directed edges that connects the node to another node of the procedural media generator; and generating a media asset using the procedural media generator.

公开(公告)号：US11189060B2

公开(公告)日：2021-11-30

申请号：US16863540

申请日：2020-04-30

Applicant: Adobe Inc.

Inventor： Milos Hasan ,  Liang Shi ,  Tamy Boubekeur ,  Kalyan Sunkavalli ,  Radomir Mech

IPC: G06T11/00 ,  G06T11/40 ,  G06T15/04 ,  G06N3/08

Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.

公开(公告)号：US20240404244A1

公开(公告)日：2024-12-05

申请号：US18329385

申请日：2023-06-05

Applicant: Adobe Inc.

Inventor： Valentin Mathieu Deschaintre ,  Yiwei Hu ,  Paul Guerrero ,  Milos Hasan

IPC: G06V10/74 ,  G06V10/44 ,  G06V10/54

Abstract: Conditional procedural model generation techniques are described that enable generation of procedural models that are usable to recreate a visual appearance of an input image. A content processing system, for instance, receives a training dataset that includes a plurality of training pairs. The content processing system trains a machine learning model to generate procedural models based on input images. The content processing system then receives an input image that has a particular visual appearance. The content processing system leverages the trained machine learning model to generate a procedural model that is usable to recreate the particular visual appearance of the input digital image.

公开(公告)号：US20240338888A1

公开(公告)日：2024-10-10

申请号：US18132714

申请日：2023-04-10

Applicant: Adobe Inc.

Inventor： Krishna Bhargava Mullia Lakshminarayana ,  Valentin Deschaintre ,  Nathan Carr ,  Milos Hasan ,  Bailey Miller

IPC: G06T15/50 ,  G06T9/00 ,  G06T15/04 ,  G06T17/20

CPC classification number: G06T15/50 ,  G06T9/001 ,  G06T15/04 ,  G06T17/20

Abstract: Certain aspects and features of this disclosure relate to rendering images by training a neural material and applying the material map to a coarse geometry to provide high-fidelity asset encoding. For example, training can involve sampling for a set of lighting and camera configurations arranged to render an image of a target asset. A value for a loss function comparing the target asset with the neural material can be optimized to train the neural material to encode a high-fidelity model of the target asset. This technique restricts the application of the neural material to a specific predetermined geometry, resulting in a reproducible asset that can be used efficiently. Such an asset can be deployed, as examples, to mobile devices or to the web, where the computational budget is limited, and nevertheless produce highly detailed images.

公开(公告)号：US11816779B2

公开(公告)日：2023-11-14

申请号：US17538311

申请日：2021-11-30

Applicant: Adobe Inc. ,  The Regents of the University of California

Inventor： Krishna Bhargava Mullia Lakshminarayana ,  Zexiang Xu ,  Milos Hasan ,  Ravi Ramamoorthi ,  Alexandr Kuznetsov

IPC: G06T15/04 ,  G06T15/55 ,  G06N3/045

CPC classification number: G06T15/04 ,  G06N3/045 ,  G06T15/55

Abstract: Methods and systems disclosed herein relate generally to surface-rendering neural networks to represent and render a variety of material appearances (e.g., textured surfaces) at different scales. The system includes receiving image metadata for a texel that includes position, incoming and outgoing radiance direction, and a kernel size. The system applies a offset-prediction neural network to the query to identify an offset coordinate for the texel. The system inputs the offset coordinate to a data structure to determine a feature vector for the texel of the textured surface. The reflectance feature vector is then processed using a decoder neural network to estimate a light-reflectance value of the texel, at which the light-reflectance value is used to render the texel of the textured surface.

公开(公告)号：US20230360285A1

公开(公告)日：2023-11-09

申请号：US18341618

申请日：2023-06-26

Applicant: Adobe Inc.

Inventor： Milos Hasan ,  Liang Shi ,  Tamy Boubekeur ,  Kalyan Sunkavalli ,  Radomir Mech

IPC: G06T11/00 ,  G06T15/04 ,  G06N3/084 ,  G06T11/40

CPC classification number: G06T11/001 ,  G06T15/04 ,  G06N3/084 ,  G06T11/40

Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.

公开(公告)号：US12148089B2

公开(公告)日：2024-11-19

申请号：US17889168

申请日：2022-08-16

Applicant: Adobe Inc.

Inventor： Ankit Phogat ,  Xin Sun ,  Vineet Batra ,  Sumit Dhingra ,  Nathan A. Carr ,  Milos Hasan

IPC: G06T15/10 ,  G06T11/20 ,  G06T17/20

Abstract: Embodiments are disclosed for performing 3-D vectorization. The method includes obtaining a three-dimensional rendered image and a camera position. The method further includes obtaining a triangle mesh representing the three-dimensional rendered image. The method further involves creating a reduced triangle mesh by removing one or more triangles from the triangle mesh. The method further involves subdividing each triangle of the reduced triangle mesh into one or more subdivided triangles. The method further involves performing a mapping of each pixel of the three-dimensional rendered image to the reduced triangle mesh. The method further involves assigning a color value to each vertex of the reduced triangle mesh. The method further involves sorting each triangle of the reduced triangle mesh using a depth value of each triangle. The method further involves generating a two-dimensional triangle mesh using the sorted triangles of the reduced triangle mesh.