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    MOTION MODEL REFINEMENT BASED ON CONTACT ANALYSIS AND OPTIMIZATION
    11.
    发明申请
    MOTION MODEL REFINEMENT BASED ON CONTACT ANALYSIS AND OPTIMIZATION 有权

    公开(公告)号：US20210335028A1

    公开(公告)日：2021-10-28

    申请号：US16860411

    申请日：2020-04-28

    Applicant: Adobe Inc.

    Inventor： Jimei Yang ,  Davis Rempe ,  Bryan Russell ,  Aaron Hertzmann

    IPC: G06T13/40 ,  G06N3/08 ,  G06T15/50 ,  G06T15/20

    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.

    MIXING SEGMENTATION ALGORITHMS UTILIZING SOFT CLASSIFICATIONS TO IDENTIFY SEGMENTS OF THREE-DIMENSIONAL DIGITAL MODELS
    14.
    发明申请
    MIXING SEGMENTATION ALGORITHMS UTILIZING SOFT CLASSIFICATIONS TO IDENTIFY SEGMENTS OF THREE-DIMENSIONAL DIGITAL MODELS 审中-公开

    公开(公告)号：US20200320715A1

    公开(公告)日：2020-10-08

    申请号：US16907663

    申请日：2020-06-22

    Applicant: ADOBE INC.

    Inventor： Vladimir Kim ,  Aaron Hertzmann ,  Mehmet Yumer

    IPC: G06T7/143 ,  G06K9/68 ,  G06K9/34 ,  G06K9/00 ,  G06T7/11

    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.

    Generating stylized-stroke images from source images utilizing style-transfer-neural networks with non-photorealistic-rendering
    15.
    发明授权
    Generating stylized-stroke images from source images utilizing style-transfer-neural networks with non-photorealistic-rendering 有权

    公开(公告)号：US10748324B2

    公开(公告)日：2020-08-18

    申请号：US16184289

    申请日：2018-11-08

    Applicant: Adobe Inc.

    Inventor： Elya Shechtman ,  Yijun Li ,  Chen Fang ,  Aaron Hertzmann

    IPC: G06T15/02 ,  G06T15/80 ,  G06N3/08 ,  G06N3/04

    Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that integrate (or embed) a non-photorealistic rendering (“NPR”) generator with a style-transfer-neural network to generate stylized images that both correspond to a source image and resemble a stroke style. By integrating an NPR generator with a style-transfer-neural network, the disclosed methods, non-transitory computer readable media, and systems can accurately capture a stroke style resembling one or both of stylized edges or stylized shadings. When training such a style-transfer-neural network, the integrated NPR generator can enable the disclosed methods, non-transitory computer readable media, and systems to use real-stroke drawings (instead of conventional paired-ground-truth drawings) for training the network to accurately portray a stroke style. In some implementations, the disclosed methods, non-transitory computer readable media, and systems can either train or apply a style-transfer-neural network that captures a variety of stroke styles, such as different edge-stroke styles or shading-stroke styles.

    Three-dimensional segmentation of digital models utilizing soft classification geometric tuning
    16.
    发明授权
    Three-dimensional segmentation of digital models utilizing soft classification geometric tuning 有权

    公开(公告)号：US10706554B2

    公开(公告)日：2020-07-07

    申请号：US15487813

    申请日：2017-04-14

    Applicant: Adobe Inc.

    Inventor： Vladimir Kim ,  Aaron Hertzmann ,  Mehmet Yumer

    IPC: G06T7/143 ,  G06K9/68 ,  G06K9/34 ,  G06K9/00 ,  G06T7/11

    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.

    Contact-aware retargeting of motion
    17.
    发明授权
    Contact-aware retargeting of motion 有权

    公开(公告)号：US12033261B2

    公开(公告)日：2024-07-09

    申请号：US17385559

    申请日：2021-07-26

    Applicant: Adobe Inc.

    Inventor： Ruben Villegas ,  Jun Saito ,  Jimei Yang ,  Duygu Ceylan Aksit ,  Aaron Hertzmann

    IPC: G06T13/40 ,  G06N3/04 ,  G06N20/00 ,  G06T7/215 ,  G06T9/00 ,  G06V40/10

    CPC classification number: G06T13/40 ,  G06N3/04 ,  G06N20/00 ,  G06T7/215 ,  G06T9/00 ,  G06V40/103

    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.

    GENERATION OF STYLIZED DRAWING OF THREE-DIMENSIONAL SHAPES USING NEURAL NETWORKS
    18.
    发明公开
    GENERATION OF STYLIZED DRAWING OF THREE-DIMENSIONAL SHAPES USING NEURAL NETWORKS 审中-公开

    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.

    MOTION MODEL REFINEMENT BASED ON CONTACT ANALYSIS AND OPTIMIZATION
    19.
    发明申请
    MOTION MODEL REFINEMENT BASED ON CONTACT ANALYSIS AND OPTIMIZATION 有权

    公开(公告)号：US20220139019A1

    公开(公告)日：2022-05-05

    申请号：US17573890

    申请日：2022-01-12

    Applicant: Adobe Inc.

    Inventor： Jimei Yang ,  Davis Rempe ,  Bryan Russell ,  Aaron Hertzmann

    IPC: G06T13/40 ,  G06N3/08 ,  G06T15/50 ,  G06T15/20

    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.

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