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公开(公告)号：US20210312599A1
公开(公告)日：2021-10-07
申请号：US17350136
申请日：2021-06-17
Applicant: ADOBE INC.
Inventor： Sohrab Amirghodsi , Elya Shechtman , Derek Novo
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for automatically synthesizing a content-aware sampling region for a hole-filling algorithm such as content-aware fill. Given a source image and a hole (or other target region to fill), a sampling region can be synthesized by identifying a band of pixels surrounding the hole, clustering these pixels based on one or more characteristics (e.g., color, x/y coordinates, depth, focus, etc.), passing each of the resulting clusters as foreground pixels to a segmentation algorithm, and unioning the resulting pixels to form the sampling region. The sampling region can be stored in a constraint mask and passed to a hole-filling algorithm such as content-aware fill to synthesize a fill for the hole (or other target region) from patches sampled from the synthesized sampling region.
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公开(公告)号：US11138693B2
公开(公告)日：2021-10-05
申请号：US16752030
申请日：2020-01-24
Applicant: Adobe Inc.
Inventor： Youssef Alami Mejjati , Zoya Bylinskii , Elya Shechtman
Abstract: Techniques of adjusting the salience of an image include generating values of photographic development parameters for a foreground and background of an image to adjust the salience of the image in the foreground. These parameters are global in nature over the image rather than local. Moreover, the optimization of the salience over such sets of global parameters is provided through two sets of these parameters by an encoder: one set corresponding to the foreground, in which the salience is to be either increased or decreased, and the other set corresponding to the background. Once the set of development parameters corresponding to the foreground region and the set of development parameters corresponding to the background region have been determined, a decoder generates an adjusted image with an increased salience based on these sets of development parameters.
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公开(公告)号：US11094083B2
公开(公告)日：2021-08-17
申请号：US16257495
申请日：2019-01-25
Applicant: Adobe Inc.
Inventor： Jonathan Eisenmann , Wenqi Xian , Matthew Fisher , Geoffrey Oxholm , Elya Shechtman
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a critical edge detection neural network and a geometric model to determine camera parameters from a single digital image. In particular, in one or more embodiments, the disclosed systems can train and utilize a critical edge detection neural network to generate a vanishing edge map indicating vanishing lines from the digital image. The system can then utilize the vanishing edge map to more accurately and efficiently determine camera parameters by applying a geometric model to the vanishing edge map. Further, the system can generate ground truth vanishing line data from a set of training digital images for training the critical edge detection neural network.
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公开(公告)号：US20210248801A1
公开(公告)日：2021-08-12
申请号：US16788551
申请日：2020-02-12
Applicant: ADOBE INC.
Inventor： Dingzeyu Li , Yang Zhou , Jose Ignacio Echevarria Vallespi , Elya Shechtman
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for generating an animation of a talking head from an input audio signal of speech and a representation (such as a static image) of a head to animate. Generally, a neural network can learn to predict a set of 3D facial landmarks that can be used to drive the animation. In some embodiments, the neural network can learn to detect different speaking styles in the input speech and account for the different speaking styles when predicting the 3D facial landmarks. Generally, template 3D facial landmarks can be identified or extracted from the input image or other representation of the head, and the template 3D facial landmarks can be used with successive windows of audio from the input speech to predict 3D facial landmarks and generate a corresponding animation with plausible 3D effects.
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公开(公告)号：US11081139B2
公开(公告)日：2021-08-03
申请号：US16378906
申请日：2019-04-09
Applicant: Adobe Inc.
Inventor： Geoffrey Oxholm , Oliver Wang , Elya Shechtman , Michal Lukac , Ramiz Sheikh
Abstract: Certain aspects involve video inpainting via confidence-weighted motion estimation. For instance, a video editor accesses video content having a target region to be modified in one or more video frames. The video editor computes a motion for a boundary of the target region. The video editor interpolates, from the boundary motion, a target motion of a target pixel within the target region. In the interpolation, confidence values assigned to boundary pixels control how the motion of these pixels contributes to the interpolated target motion. A confidence value is computed based on a difference between forward and reverse motion with respect to a particular boundary pixel, a texture in a region that includes the particular boundary pixel, or a combination thereof. The video editor modifies the target region in the video by updating color data of the target pixel to correspond to the target motion interpolated from the boundary motion.
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Patent Agency Ranking
公开(公告)号：US11042969B2
公开(公告)日：2021-06-22
申请号：US16420782
申请日：2019-05-23
Applicant: ADOBE INC.
Inventor： Sohrab Amirghodsi , Elya Shechtman , Derek Novo
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for automatically synthesizing a content-aware sampling region for a hole-filling algorithm such as content-aware fill. Given a source image and a hole (or other target region to fill), a sampling region can be synthesized by identifying a band of pixels surrounding the hole, clustering these pixels based on one or more characteristics (e.g., color, x/y coordinates, depth, focus, etc.), passing each of the resulting clusters as foreground pixels to a segmentation algorithm, and unioning the resulting pixels to form the sampling region. The sampling region can be stored in a constraint mask and passed to a hole-filling algorithm such as content-aware fill to synthesize a fill for the hole (or other target region) from patches sampled from the synthesized sampling region.
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公开(公告)号：US20210142463A1
公开(公告)日：2021-05-13
申请号：US16678132
申请日：2019-11-08
Applicant: Adobe Inc.
Inventor： Sohrab Amirghodsi , Aliakbar Darabi , Elya Shechtman
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating modified digital images by utilizing a patch match algorithm to generate nearest neighbor fields for a second digital image based on a nearest neighbor field associated with a first digital image. For example, the disclosed systems can identify a nearest neighbor field associated with a first digital image of a first resolution. Based on the nearest neighbor field of the first digital image, the disclosed systems can utilize a patch match algorithm to generate a nearest neighbor field for a second digital image of a second resolution larger than the first resolution. The disclosed systems can further generate a modified digital image by filling a target region of the second digital image utilizing the generated nearest neighbor field.
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公开(公告)号：US20210056668A1
公开(公告)日：2021-02-25
申请号：US16548498
申请日：2019-08-22
Applicant: Adobe Inc.
Inventor： Connelly Barnes , Sohrab Amirghodsi , Elya Shechtman
Abstract: Techniques are disclosed for filling or otherwise replacing a target region of a primary image with a corresponding region of an auxiliary image. The filling or replacing can be done with an overlay (no subtractive process need be run on the primary image). Because the primary and auxiliary images may not be aligned, both geometric and photometric transformations are applied to the primary and/or auxiliary images. For instance, a geometric transformation of the auxiliary image is performed, to better align features of the auxiliary image with corresponding features of the primary image. Also, a photometric transformation of the auxiliary image is performed, to better match color of one or more pixels of the auxiliary image with color of corresponding one or more pixels of the primary image. The corresponding region of the transformed auxiliary image is then copied and overlaid on the target region of the primary image.
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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
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.
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190.发明申请公开(公告)号：US20200242804A1
公开(公告)日：2020-07-30
申请号：US16257495
申请日：2019-01-25
Applicant: Adobe Inc.
Inventor： Jonathan Eisenmann , Wenqi Xian , Matthew Fisher , Geoffrey Oxholm , Elya Shechtman
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a critical edge detection neural network and a geometric model to determine camera parameters from a single digital image. In particular, in one or more embodiments, the disclosed systems can train and utilize a critical edge detection neural network to generate a vanishing edge map indicating vanishing lines from the digital image. The system can then utilize the vanishing edge map to more accurately and efficiently determine camera parameters by applying a geometric model to the vanishing edge map. Further, the system can generate ground truth vanishing line data from a set of training digital images for training the critical edge detection neural network.
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