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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.
Inventor： Ruben Villegas , Jun Saito , Jimei Yang , Duygu Ceylan Aksit , Aaron Hertzmann
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.
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公开(公告)号：US20220284640A1
公开(公告)日：2022-09-08
申请号：US17664800
申请日：2022-05-24
Applicant: Adobe Inc.
Inventor： Xin Sun , Ruben Villegas , Manuel Lagunas Arto , Jimei Yang , Jianming Zhang
Abstract: 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：US11334971B2
公开(公告)日：2022-05-17
申请号：US16928340
申请日：2020-07-14
Applicant: Adobe Inc.
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
Abstract: 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：US20210295571A1
公开(公告)日：2021-09-23
申请号：US16823092
申请日：2020-03-18
Applicant: Adobe Inc.
Inventor： Xin Sun , Ruben Villegas , Manuel Lagunas Arto , Jimei Yang , Jianming Zhang
Abstract: 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：US10922860B2
公开(公告)日：2021-02-16
申请号：US16410854
申请日：2019-05-13
Applicant: Adobe Inc.
Inventor： Brian Price , Ning Xu , Naoto Inoue , Jimei Yang , Daicho Ito
Abstract: Computing systems and computer-implemented methods can be used for automatically generating a digital line drawing of the contents of a photograph. In various examples, these techniques include use of a neural network, referred to as a generator network, that is trained on a dataset of photographs and human-generated line drawings of the photographs. The training data set teaches the neural network to trace the edges and features of objects in the photographs, as well as which edges or features can be ignored. The output of the generator network is a two-tone digital image, where the background of the image is one tone, and the contents in the input photographs are represented by lines drawn in the second tone. In some examples, a second neural network, referred to as a restorer network, can further process the output of the generator network, and remove visual artifacts and clean up the lines.
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Patent Agency Ranking
公开(公告)号：US10922852B2
公开(公告)日：2021-02-16
申请号：US16539187
申请日：2019-08-13
Applicant: Adobe Inc.
Inventor： Zhili Chen , Zhaowen Wang , Rundong Wu , Jimei Yang
Abstract: Oil painting simulation techniques are disclosed which simulate painting brush strokes using a trained neural network. In some examples, a method may include inferring a new height map of existing paint on a canvas after a new painting brush stroke is applied based on a bristle trajectory map that represents the new painting brush stroke and a height map of existing paint on the canvas prior to the application of the new painting brush stroke, and generating a rendering of the new painting brush stroke based on the new height map of existing paint on the canvas after the new painting brush stroke is applied to the canvas and a color map.
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公开(公告)号：US20200327675A1
公开(公告)日：2020-10-15
申请号：US16384039
申请日：2019-04-15
Applicant: Adobe Inc.
Inventor： Zhe Lin , Wei Xiong , Connelly Barnes , Jimei Yang , Xin Lu
Abstract: 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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38.发明授权公开(公告)号：US10769764B2
公开(公告)日：2020-09-08
申请号：US16271058
申请日：2019-02-08
Applicant: Adobe Inc.
Inventor： Chen Fang , Zhe Lin , Zhaowen Wang , Yulun Zhang , Yilin Wang , Jimei Yang
Abstract: A style of a digital image is transferred to another digital image of arbitrary resolution. A high-resolution (HR) content image is segmented into several low-resolution (LR) patches. The resolution of a style image is matched to have the same resolution as the LR content image patches. Style transfer is then performed on a patch-by-patch basis using, for example, a pair of feature transforms—whitening and coloring. The patch-by-patch style transfer process is then repeated at several increasing resolutions, or scale levels, of both the content and style images. The results of the style transfer at each scale level are incorporated into successive scale levels up to and including the original HR scale. As a result, style transfer can be performed with images having arbitrary resolutions to produce visually pleasing results with good spatial consistency.
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公开(公告)号：US10755391B2
公开(公告)日：2020-08-25
申请号：US15980691
申请日：2018-05-15
Applicant: Adobe Inc.
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
Abstract: 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：US20190355102A1
公开(公告)日：2019-11-21
申请号：US15980691
申请日：2018-05-15
Applicant: Adobe Inc.
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
Abstract: 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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