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公开(公告)号：US20240046566A1
公开(公告)日：2024-02-08
申请号：US17816813
申请日：2022-08-02
申请人： ADOBE INC.
发明人： Jimei Yang , Chun-han Yao , Duygu Ceylan Aksit , Yi Zhou
IPC分类号： G06T17/20
CPC分类号： G06T17/20
摘要： Systems and methods for mesh generation are described. One aspect of the systems and methods includes receiving an image depicting a visible portion of a body; generating an intermediate mesh representing the body based on the image; generating visibility features indicating whether parts of the body are visible based on the image; generating parameters for a morphable model of the body based on the intermediate mesh and the visibility features; and generating an output mesh representing the body based on the parameters for the morphable model, wherein the output mesh includes a non-visible portion of the body that is not depicted by the image.
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2.发明公开公开(公告)号：US20230360320A1
公开(公告)日：2023-11-09
申请号：US18354619
申请日：2023-07-18
申请人： Adobe Inc.
发明人： Ruben Villegas , Yunseok Jang , Duygu Ceylan Aksit , Jimei Yang , Xin Sun
摘要： This disclosure describes methods, non-transitory computer readable storage media, and systems that generate realistic shading for three-dimensional objects inserted into digital images. The disclosed system utilizes a light encoder neural network to generate a representation embedding of lighting in a digital image. Additionally, the disclosed system determines points of the three-dimensional object visible within a camera view. The disclosed system generates a self-occlusion map for the digital three-dimensional object by determining whether fixed sets of rays uniformly sampled from the points intersects with the digital three-dimensional object. The disclosed system utilizes a generator neural network to determine a shading map for the digital three-dimensional object based on the representation embedding of lighting in the digital image and the self-occlusion map. Additionally, the disclosed system generates a modified digital image with the three-dimensional object inserted into the digital image with consistent lighting of the three-dimensional object and the digital image.
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公开(公告)号：US11657546B2
公开(公告)日：2023-05-23
申请号：US17664800
申请日：2022-05-24
申请人： Adobe Inc.
发明人： Xin Sun , Ruben Villegas , Manuel Lagunas Arto , Jimei Yang , Jianming Zhang
CPC分类号： G06T11/001 , G06T7/11 , G06T7/194 , G06T7/90 , G06T2207/20084 , G06T2207/30196
摘要： Introduced here are techniques for relighting an image by automatically segmenting a human object in an image. The segmented image is input to an encoder that transforms it into a feature space. The feature space is concatenated with coefficients of a target illumination for the image and input to an albedo decoder and a light transport detector to predict an albedo map and a light transport matrix, respectively. In addition, the output of the encoder is concatenated with outputs of residual parts of each decoder and fed to a light coefficients block, which predicts coefficients of the illumination for the image. The light transport matrix and predicted illumination coefficients are multiplied to obtain a shading map that can sharpen details of the image. Scaling the resulting image by the albedo map to produce the relight image. The relight image can be refined to denoise the relight image.
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公开(公告)号：US11238634B2
公开(公告)日：2022-02-01
申请号：US16860411
申请日：2020-04-28
申请人： Adobe Inc.
发明人： Jimei Yang , Davis Rempe , Bryan Russell , Aaron Hertzmann
摘要： 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.
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公开(公告)号：US20210343059A1
公开(公告)日：2021-11-04
申请号：US16864724
申请日：2020-05-01
申请人： Adobe Inc.
摘要： Motion retargeting with kinematic constraints is implemented in a digital medium environment. Generally, the described techniques provide for retargeting motion data from a source motion sequence to a target visual object. Accordingly, the described techniques position a target visual object in a defined visual environment to identify kinematic constraints of the target object relative to the visual environment. Further, the described techniques utilize an iterative optimization process that fine tunes the conformance of retargeted motion of a target object to the identified kinematic constraints.
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公开(公告)号：US10964100B2
公开(公告)日：2021-03-30
申请号：US16126552
申请日：2018-09-10
申请人： Adobe Inc.
发明人： Xin Sun , Zhili Chen , Nathan Carr , Julio Marco Murria , Jimei Yang
摘要： According to one general aspect, systems and techniques for rendering a painting stroke of a three-dimensional digital painting include receiving a painting stroke input on a canvas, where the painting stroke includes a plurality of pixels. For each of the pixels in the plurality of pixels, a neighborhood patch of pixels is selected and input into a neural network and a shading function is output from the neural network. The painting stroke is rendered on the canvas using the shading function.
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公开(公告)号：US10964084B2
公开(公告)日：2021-03-30
申请号：US16451813
申请日：2019-06-25
申请人： Adobe Inc.
发明人： Jingwan Lu , Yi Zhou , Connelly Barnes , Jimei Yang
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a digital animation of a digital animation character by utilizing a generative adversarial network and a hip motion prediction network. For example, the disclosed systems can utilize an unconditional generative adversarial network to generate a sequence of local poses of a digital animation character based on an input of a random code vector. The disclosed systems can also utilize a conditional generative adversarial network to generate a sequence of local poses based on an input of a set of keyframes. Based on the sequence of local poses, the disclosed systems can utilize a hip motion prediction network to generate a sequence of global poses based on hip velocities. In addition, the disclosed systems can generate an animation of a digital animation character based on the sequence of global poses.
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公开(公告)号：US20210082124A1
公开(公告)日：2021-03-18
申请号：US17103119
申请日：2020-11-24
申请人： Adobe Inc.
发明人： Zhe Lin , Wei Xiong , Connelly Barnes , Jimei Yang , Xin Lu
摘要： In some embodiments, an image manipulation application receives an incomplete image that includes a hole area lacking image content. The image manipulation application applies a contour detection operation to the incomplete image to detect an incomplete contour of a foreground object in the incomplete image. The hole area prevents the contour detection operation from detecting a completed contour of the foreground object. The image manipulation application further applies a contour completion model to the incomplete contour and the incomplete image to generate the completed contour for the foreground object. Based on the completed contour and the incomplete image, the image manipulation application generates image content for the hole area to generate a completed image.
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公开(公告)号：US20200342576A1
公开(公告)日：2020-10-29
申请号：US16928340
申请日：2020-07-14
申请人： Adobe Inc.
发明人： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
摘要： Digital image completion by learning generation and patch matching jointly is described. Initially, a digital image having at least one hole is received. This holey digital image is provided as input to an image completer formed with a dual-stage framework that combines a coarse image neural network and an image refinement network. The coarse image neural network generates a coarse prediction of imagery for filling the holes of the holey digital image. The image refinement network receives the coarse prediction as input, refines the coarse prediction, and outputs a filled digital image having refined imagery that fills these holes. The image refinement network generates refined imagery using a patch matching technique, which includes leveraging information corresponding to patches of known pixels for filtering patches generated based on the coarse prediction. Based on this, the image completer outputs the filled digital image with the refined imagery.
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公开(公告)号：US20200184610A1
公开(公告)日：2020-06-11
申请号：US16791939
申请日：2020-02-14
申请人： Adobe Inc.
发明人： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
摘要： Digital image completion using deep learning is described. Initially, a digital image having at least one hole is received. This holey digital image is provided as input to an image completer formed with a framework that combines generative and discriminative neural networks based on learning architecture of the generative adversarial networks. From the holey digital image, the generative neural network generates a filled digital image having hole-filling content in place of holes. The discriminative neural networks detect whether the filled digital image and the hole-filling digital content correspond to or include computer-generated content or are photo-realistic. The generating and detecting are iteratively continued until the discriminative neural networks fail to detect computer-generated content for the filled digital image and hole-filling content or until detection surpasses a threshold difficulty. Responsive to this, the image completer outputs the filled digital image with hole-filling content in place of the holey digital image's holes.
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