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公开(公告)号：US20190287224A1
公开(公告)日：2019-09-19
申请号：US15921447
申请日：2018-03-14
Applicant: ADOBE INC.
Inventor： Sohrab Amirghodsi , Sarah Jane Stuckey , Elya Shechtman
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for automatically synthesizing a content-aware fill using similarity transformed patches. A user interface receives a user-specified hole and a user-specified sampling region, both of which may be stored in a constraint mask. A brush tool can be used to interactively brush the sampling region and modify the constraint mask. The mask is passed to a patch-based synthesizer configured to synthesize the fill using similarity transformed patches sampled from the sampling region. Fill properties such as similarity transform parameters can be set to control the manner in which the fill is synthesized. A live preview can be provided with gradual updates of the synthesized fill prior to completion. Once a fill has been synthesized, the user interface presents the original image, replacing the hole with the synthesized fill.
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公开(公告)号：US20190251401A1
公开(公告)日：2019-08-15
申请号：US15897910
申请日：2018-02-15
Applicant: Adobe Inc.
Inventor： Elya Shechtman , Oliver Wang , Mehmet Yumer , Chen-Hsuan Lin
Abstract: The present disclosure relates to an image composite system that employs a generative adversarial network to generate realistic composite images. For example, in one or more embodiments, the image composite system trains a geometric prediction neural network using an adversarial discrimination neural network to learn warp parameters that provide correct geometric alignment of foreground objects with respect to a background image. Once trained, the determined warp parameters provide realistic geometric corrections to foreground objects such that the warped foreground objects appear to blend into background images naturally when composited together.
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73.发明申请公开(公告)号：US20250139748A1
公开(公告)日：2025-05-01
申请号：US19011235
申请日：2025-01-06
Applicant: Adobe Inc.
Inventor： Sohrab Amirghodsi , Lingzhi Zhang , Zhe Lin , Connelly Barnes , Elya Shechtman
IPC: G06T5/77 , G06N3/08 , G06T3/4053 , G06T7/11 , G06T7/50
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly generating modified digital images utilizing a guided inpainting approach that implements a patch match model informed by a deep visual guide. In particular, the disclosed systems can utilize a visual guide algorithm to automatically generate guidance maps to help identify replacement pixels for inpainting regions of digital images utilizing a patch match model. For example, the disclosed systems can generate guidance maps in the form of structure maps, depth maps, or segmentation maps that respectively indicate the structure, depth, or segmentation of different portions of digital images. Additionally, the disclosed systems can implement a patch match model to identify replacement pixels for filling regions of digital images according to the structure, depth, and/or segmentation of the digital images.
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74.发明申请公开(公告)号：US20250124544A1
公开(公告)日：2025-04-17
申请号：US18487764
申请日：2023-10-16
Applicant: ADOBE INC.
Inventor： Taesung Park , Qing Liu , Zhe Lin , Sohrab Amirghodsi , Elya Shechtman
Abstract: Systems and methods for upsampling low-resolution content within a high-resolution image include obtaining a composite image and a mask. The composite image includes a high-resolution region and a low-resolution region. An upsampling network identifies the low-resolution region of the composite image based on the mask and generates an upsampled composite image based on the composite image and the mask. The upsampled composite image comprises higher frequency details in the low-resolution region than the composite image.
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公开(公告)号：US12272031B2
公开(公告)日：2025-04-08
申请号：US17725818
申请日：2022-04-21
Applicant: Adobe Inc.
Inventor： Krishna Kumar Singh , Yuheng Li , Yijun Li , Jingwan Lu , Elya Shechtman
Abstract: An image inpainting system is described that receives an input image that includes a masked region. From the input image, the image inpainting system generates a synthesized image that depicts an object in the masked region by selecting a first code that represents a known factor characterizing a visual appearance of the object and a second code that represents an unknown factor characterizing the visual appearance of the object apart from the known factor in latent space. The input image, the first code, and the second code are provided as input to a generative adversarial network that is trained to generate the synthesized image using contrastive losses. Different synthesized images are generated from the same input image using different combinations of first and second codes, and the synthesized images are output for display.
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Patent Agency Ranking
公开(公告)号：US12254594B2
公开(公告)日：2025-03-18
申请号：US17657691
申请日：2022-04-01
Applicant: Adobe Inc.
Inventor： Hui Qu , Jingwan Lu , Saeid Motiian , Shabnam Ghadar , Wei-An Lin , Elya Shechtman
Abstract: Methods, systems, and non-transitory computer readable media are disclosed for intelligently enhancing details in edited images. The disclosed system iteratively updates residual detail latent code for segments in edited images where detail has been lost through the editing process. More particularly, the disclosed system enhances an edited segment in an edited image based on details in a detailed segment of an image. Additionally, the disclosed system may utilize a detail neural network encoder to project the detailed segment and a corresponding segment of the edited image into a residual detail latent code. In some embodiments, the disclosed system generates a refined edited image based on the residual detail latent code and a latent vector of the edited image.
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公开(公告)号：US12249051B2
公开(公告)日：2025-03-11
申请号：US17651435
申请日：2022-02-17
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：US20250069299A1
公开(公告)日：2025-02-27
申请号：US18452827
申请日：2023-08-21
Applicant: ADOBE INC.
Inventor： Kevin Duarte , Wei-An Lin , Ratheesh Kalarot , Shabnam Ghadar , Jingwan Lu , Elya Shechtman
IPC: G06T11/60
Abstract: One or more aspects of a method, apparatus, and non-transitory computer readable medium include obtaining an input latent vector for an image generation network and a target lighting representation. A modified latent vector is generated based on the input latent vector and the target lighting representation, and an image generation network generates an image based on the modified latent vector using.
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79.发明申请公开(公告)号：US20250054116A1
公开(公告)日：2025-02-13
申请号：US18929330
申请日：2024-10-28
Applicant: Adobe Inc.
Inventor： Haitian Zheng , Zhe Lin , Jingwan Lu , Scott Cohen , Elya Shechtman , Connelly Barnes , Jianming Zhang , Ning Xu , Sohrab Amirghodsi
IPC: G06T5/77 , G06T3/4046 , G06V10/40
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that generate inpainted digital images utilizing a cascaded modulation inpainting neural network. For example, the disclosed systems utilize a cascaded modulation inpainting neural network that includes cascaded modulation decoder layers. For example, in one or more decoder layers, the disclosed systems start with global code modulation that captures the global-range image structures followed by an additional modulation that refines the global predictions. Accordingly, in one or more implementations, the image inpainting system provides a mechanism to correct distorted local details. Furthermore, in one or more implementations, the image inpainting system leverages fast Fourier convolutions block within different resolution layers of the encoder architecture to expand the receptive field of the encoder and to allow the network encoder to better capture global structure.
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公开(公告)号：US20250045994A1
公开(公告)日：2025-02-06
申请号：US18924508
申请日：2024-10-23
Applicant: Adobe Inc.
Inventor： Nadav Epstein , Alexei A Efros , Taesung Park , Richard Zhang , Elya Shechtman
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating digital images depicting photorealistic scenes utilizing a digital image collaging neural network. For example, the disclosed systems utilize a digital image collaging neural network having a particular architecture for disentangling generation of scene layouts and pixel colors for different regions of a digital image. In some cases, the disclosed systems break down the process of generating a collage digital into generating images representing different regions such as a background and a foreground to be collaged into a final result. For example, utilizing the digital image collaging neural network, the disclosed systems determine scene layouts and pixel colors for both foreground digital images and background digital images to ultimately collage the foreground and background together into a collage digital image depicting a real-world scene.
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