Accurate smooth occluding contours

    公开(公告)号:US11941746B2

    公开(公告)日:2024-03-26

    申请号:US17466670

    申请日:2021-09-03

    Applicant: Adobe Inc.

    CPC classification number: G06T15/20 G06T7/564 G06T17/205

    Abstract: Embodiments are disclosed for computing accurate smooth occluding contours. In one embodiment, a method of computing accurate smooth occluding contours includes projecting a boundary polygon associated with a first region of a three-dimensional (3D) object to a two-dimensional (2D) image plane, the boundary polygon comprising a plurality of contour vertices and edges connecting the plurality of contour vertices, triangulating the first region in the 2D image plane to generate a 2D triangulation, and generating a 3D mesh for the first region by mapping the 2D triangulation to the 3D object.

    Mixing segmentation algorithms utilizing soft classifications to identify segments of three-dimensional digital models

    公开(公告)号:US11315255B2

    公开(公告)日:2022-04-26

    申请号:US16907663

    申请日:2020-06-22

    Applicant: ADOBE INC.

    Abstract: The present disclosure includes methods and systems for identifying and manipulating a segment of a three-dimensional digital model based on soft classification of the three-dimensional digital model. In particular, one or more embodiments of the disclosed systems and methods identify a soft classification of a digital model and utilize the soft classification to tune segmentation algorithms. For example, the disclosed systems and methods can utilize a soft classification to select a segmentation algorithm from a plurality of segmentation algorithms, to combine segmentation parameters from a plurality of segmentation algorithms, and/or to identify input parameters for a segmentation algorithm. The disclosed systems and methods can utilize the tuned segmentation algorithms to accurately and efficiently identify a segment of a three-dimensional digital model.

    Motion model refinement based on contact analysis and optimization

    公开(公告)号:US11238634B2

    公开(公告)日:2022-02-01

    申请号:US16860411

    申请日:2020-04-28

    Applicant: Adobe Inc.

    Abstract: In some embodiments, a motion model refinement system receives an input video depicting a human character and an initial motion model describing motions of individual joint points of the human character in a three-dimensional space. The motion model refinement system identifies foot joint points of the human character that are in contact with a ground plane using a trained contact estimation model. The motion model refinement system determines the ground plane based on the foot joint points and the initial motion model and constructs an optimization problem for refining the initial motion model. The optimization problem minimizes the difference between the refined motion model and the initial motion model under a set of plausibility constraints including constraints on the contact foot joint points and a time-dependent inertia tensor-based constraint. The motion model refinement system obtains the refined motion model by solving the optimization problem.

    Generation of stylized drawing of three-dimensional shapes using neural networks

    公开(公告)号:US11880913B2

    公开(公告)日:2024-01-23

    申请号:US17452568

    申请日:2021-10-27

    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.

    CONTACT-AWARE RETARGETING OF MOTION

    公开(公告)号:US20230037339A1

    公开(公告)日:2023-02-09

    申请号:US17385559

    申请日:2021-07-26

    Applicant: Adobe Inc.

    Abstract: One example method involves a processing device that performs operations that include receiving a request to retarget a source motion into a target object. Operations further include providing the target object to a contact-aware motion retargeting neural network trained to retarget the source motion into the target object. The contact-aware motion retargeting neural network is trained by accessing training data that includes a source object performing the source motion. The contact-aware motion retargeting neural network generates retargeted motion for the target object, based on a self-contact having a pair of input vertices. The retargeted motion is subject to motion constraints that: (i) preserve a relative location of the self-contact and (ii) prevent self-penetration of the target object.

    Motion model refinement based on contact analysis and optimization

    公开(公告)号:US11721056B2

    公开(公告)日:2023-08-08

    申请号:US17573890

    申请日:2022-01-12

    Applicant: Adobe Inc.

    CPC classification number: G06T13/40 G06N3/08 G06T15/20 G06T15/50

    Abstract: In some embodiments, a model training system obtains a set of animation models. For each of the animation models, the model training system renders the animation model to generate a sequence of video frames containing a character using a set of rendering parameters and extracts joint points of the character from each frame of the sequence of video frames. The model training system further determines, for each frame of the sequence of video frames, whether a subset of the joint points are in contact with a ground plane in a three-dimensional space and generates contact labels for the subset of the joint points. The model training system trains a contact estimation model using training data containing the joint points extracted from the sequences of video frames and the generated contact labels. The contact estimation model can be used to refine a motion model for a character.

    GENERATION OF STYLIZED DRAWING OF THREE-DIMENSIONAL SHAPES USING NEURAL NETWORKS

    公开(公告)号:US20230109732A1

    公开(公告)日:2023-04-13

    申请号:US17452568

    申请日:2021-10-27

    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.

    UTILIZING SOFT CLASSIFICATIONS TO SELECT INPUT PARAMETERS FOR SEGMENTATION ALGORITHMS AND IDENTIFY SEGMENTS OF THREE-DIMENSIONAL DIGITAL MODELS

    公开(公告)号:US20220207749A1

    公开(公告)日:2022-06-30

    申请号:US17655226

    申请日:2022-03-17

    Applicant: Adobe Inc.

    Abstract: The present disclosure includes methods and systems for identifying and manipulating a segment of a three-dimensional digital model based on soft classification of the three-dimensional digital model. In particular, one or more embodiments of the disclosed systems and methods identify a soft classification of a digital model and utilize the soft classification to tune segmentation algorithms. For example, the disclosed systems and methods can utilize a soft classification to select a segmentation algorithm from a plurality of segmentation algorithms, to combine segmentation parameters from a plurality of segmentation algorithms, and/or to identify input parameters for a segmentation algorithm. The disclosed systems and methods can utilize the tuned segmentation algorithms to accurately and efficiently identify a segment of a three-dimensional digital model.

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