公开(公告)号：US10817713B2

公开(公告)日：2020-10-27

申请号：US16192573

申请日：2018-11-15

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Zhe Lin ,  Walter Chang ,  Nham Le ,  Franck Dernoncourt

IPC: G06K9/00 ,  G06N3/04 ,  G10L15/26 ,  G10L15/25

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating modified digital images based on verbal and/or gesture input by utilizing a natural language processing neural network and one or more computer vision neural networks. The disclosed systems can receive verbal input together with gesture input. The disclosed systems can further utilize a natural language processing neural network to generate a verbal command based on verbal input. The disclosed systems can select a particular computer vision neural network based on the verbal input and/or the gesture input. The disclosed systems can apply the selected computer vision neural network to identify pixels within a digital image that correspond to an object indicated by the verbal input and/or gesture input. Utilizing the identified pixels, the disclosed systems can generate a modified digital image by performing one or more editing actions indicated by the verbal input and/or gesture input.

公开(公告)号：US10810721B2

公开(公告)日：2020-10-20

申请号：US15458826

申请日：2017-03-14

Applicant: Adobe Inc.

Inventor： Radomir Mech ,  Ning Yu ,  Xiaohui Shen ,  Zhe Lin

IPC: G06T7/00 ,  G06N3/08 ,  G06N3/04

Abstract: Digital image defect identification and correction techniques are described. In one example, a digital medium environment is configured to identify and correct a digital image defect through identification of a defect in a digital image using machine learning. The identification includes generating a plurality of defect type scores using a plurality of defect type identification models, as part of machine learning, for a plurality of different defect types and determining the digital image includes the defect based on the generated plurality of defect type scores. A correction is generated for the identified defect and the digital image is output as included the generated correction.

公开(公告)号：US10810707B2

公开(公告)日：2020-10-20

申请号：US16204675

申请日：2018-11-29

Applicant: Adobe Inc.

Inventor： Jianming Zhang ,  Zhe Lin ,  Xiaohui Shen ,  Oliver Wang ,  Lijun Wang

IPC: G06T5/00 ,  G06T5/20

Abstract: Techniques of generating depth-of-field blur effects on digital images by digital effect generation system of a computing device are described. The digital effect generation system is configured to generate depth-of-field blur effects on objects based on focal depth value that defines a depth plane in the digital image and a aperture value that defines an intensity of blur effect applied to the digital image. The digital effect generation system is also configured to improve the accuracy with which depth-of-field blur effects are generated by performing up-sampling operations and implementing a unique focal loss algorithm that minimizes the focal loss within digital images effectively.

公开(公告)号：US10810252B2

公开(公告)日：2020-10-20

申请号：US15002179

申请日：2016-01-20

Applicant: ADOBE INC.

Inventor： Bernard James Kerr ,  Zhe Lin ,  Patrick Reynolds ,  Baldo Faieta

IPC: G06F17/00 ,  G06F7/00 ,  G06F16/532 ,  G06F16/56 ,  G06F16/583 ,  G06N3/08 ,  G06F3/0482 ,  G06F3/0484 ,  G06N5/02

Abstract: In various implementations, specific attributes found in images can be used in a visual-based search. Utilizing machine learning, deep neural networks, and other computer vision techniques, attributes of images, such as color, composition, font, style, and texture can be extracted from a given image. A user can then select a specific attribute from a sample image the user is searching for and the search can be refined to focus on that specific attribute from the sample image. In some embodiments, the search includes specific attributes from more than one image.

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

IPC: G06T7/149 ,  G06T7/13 ,  G06T5/00 ,  G06T7/194

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.

公开(公告)号：US20200302579A1

公开(公告)日：2020-09-24

申请号：US16893505

申请日：2020-06-05

Applicant: Adobe Inc.

Inventor： Jonathan Eisenmann ,  Zhe Lin ,  Matthew Fisher

IPC: G06T5/00 ,  G06T5/50 ,  G06T15/10 ,  G06T3/00 ,  G06T11/00

Abstract: In some embodiments, an image manipulation application receives a two-dimensional background image and projects the background image onto a sphere to generate a sphere image. Based on the sphere image, an unfilled environment map containing a hole area lacking image content can be generated. A portion of the unfilled environment map can be projected to an unfilled projection image using a map projection. The unfilled projection image contains the hole area. A hole filling model is applied to the unfilled projection image to generate a filled projection image containing image content for the hole area. A filled environment map can be generated by applying an inverse projection of the map projection on the filled projection image and by combining the unfilled environment map with the generated image content for the hole area of the environment map.

公开(公告)号：US10776671B2

公开(公告)日：2020-09-15

申请号：US15989436

申请日：2018-05-25

Applicant: Adobe Inc.

Inventor： Zhe Lin ,  Xiaohui Shen ,  Shanghang Zhang ,  Radomir Mech

IPC: G06K9/62 ,  G06K9/46 ,  G06T7/00 ,  G06N3/08

Abstract: Techniques are disclosed for blur classification. The techniques utilize an image content feature map, a blur map, and an attention map, thereby combining low-level blur estimation with a high-level understanding of important image content in order to perform blur classification. The techniques allow for programmatically determining if blur exists in an image, and determining what type of blur it is (e.g., high blur, low blur, middle or neutral blur, or no blur). According to one example embodiment, if blur is detected, an estimate of spatially-varying blur amounts is performed and blur desirability is categorized in terms of image quality.

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

IPC: G06T7/40 ,  G06T5/50 ,  G06T3/40 ,  G06T7/11 ,  G06T11/00 ,  G06T3/00

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.

公开(公告)号：US10762608B2

公开(公告)日：2020-09-01

申请号：US16119709

申请日：2018-08-31

Applicant: Adobe Inc.

Inventor： Xiaohui Shen ,  Yi-Hsuan Tsai ,  Kalyan K. Sunkavalli ,  Zhe Lin

IPC: G06F3/0482 ,  G06F3/0484 ,  G06T11/00 ,  G06T5/00 ,  G06T7/90 ,  G06F16/583

Abstract: Embodiments of the present disclosure relate to a sky editing system and related processes for sky editing. The sky editing system includes a composition detector to determine the composition of a target image. A sky search engine in the sky editing system is configured to find a reference image with similar composition with the target image. Subsequently, a sky editor replaces content of the sky in the target image with content of the sky in the reference image. As such, the sky editing system transforms the target image into a new image with a preferred sky background.

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

IPC: G06K9/62 ,  G06T5/00

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.