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211.发明申请公开(公告)号：US20190272451A1
公开(公告)日：2019-09-05
申请号：US16417115
申请日：2019-05-20
Applicant: Adobe Inc.
Inventor： Zhe Lin , Mai Long , Jonathan Brandt , Hailin Jin , Chen Fang
Abstract: The present disclosure includes methods and systems for searching for digital visual media based on semantic and spatial information. In particular, one or more embodiments of the disclosed systems and methods identify digital visual media displaying targeted visual content in a targeted region based on a query term and a query area provide via a digital canvas. Specifically, the disclosed systems and methods can receive user input of a query term and a query area and provide the query term and query area to a query neural network to generate a query feature set. Moreover, the disclosed systems and methods can compare the query feature set to digital visual media feature sets. Further, based on the comparison, the disclosed systems and methods can identify digital visual media portraying targeted visual content corresponding to the query term within a targeted region corresponding to the query area.
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公开(公告)号：US10319412B2
公开(公告)日：2019-06-11
申请号：US15353186
申请日：2016-11-16
Applicant: Adobe Inc.
Inventor： Zhihong Ding , Zhe Lin , Xiaohui Shen , Michael Kaplan , Jonathan Brandt
Abstract: The present disclosure is directed toward systems and methods for tracking objects in videos. For example, one or more embodiments described herein utilize various tracking methods in combination with an image search index made up of still video frames indexed from a video. One or more embodiments described herein utilize a backward and forward tracking method that is anchored by one or more key frames in order to accurately track an object through the frames of a video, even when the video is long and may include challenging conditions.
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公开(公告)号：US10290085B2
公开(公告)日：2019-05-14
申请号：US15379337
申请日：2016-12-14
Applicant: ADOBE INC.
Abstract: Image hole filling that account for global structure and local texture. One exemplary technique involves using both a content neural network and a texture neural network. The content neural network is trained to encode image features based on non-hole image portions and decode the image features to fill holes. The texture neural network is trained to extract image patch features that represent texture. The exemplary technique receives an input image that has a hole and uses the two neural networks to fill the hole and provide a result image. This is accomplished by selecting pixel values for the hole based on a content constraint that uses the content neural network to account for global structure and a texture constraint that uses the texture neural network to account for local texture. For example, the pixel values can be selected by optimizing a loss function that implements the constraints.
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214.发明授权公开(公告)号：US12288279B2
公开(公告)日：2025-04-29
申请号：US18058538
申请日：2022-11-23
Applicant: Adobe Inc.
Inventor： Jonathan Brandt , Scott Cohen , Zhe Lin , Zhihong Ding , Darshan Prasad , Matthew Joss , Celso Gomes , Jianming Zhang , Olena Soroka , Klaas Stoeckmann , Michael Zimmermann , Thomas Muehrke
IPC: G06T11/60 , G06F3/048 , G06F3/04842 , G06F3/04845 , G06T11/40
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems generate utilizing a segmentation neural network, an object mask for each object of a plurality of objects of a digital image. The disclosed systems detect a first user interaction with an object in the digital image displayed via a graphical user interface. The disclosed systems surface, via the graphical user interface, the object mask for the object in response to the first user interaction. The disclosed systems perform an object-aware modification of the digital image in response to a second user interaction with the object mask for the object.
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公开(公告)号：US12272127B2
公开(公告)日：2025-04-08
申请号：US17589114
申请日：2022-01-31
Applicant: Adobe Inc.
Inventor： Jason Wen Yong Kuen , Su Chen , Scott Cohen , Zhe Lin , Zijun Wei , Jianming Zhang
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates object masks for digital objects portrayed in digital images utilizing a detection-masking neural network pipeline. In particular, in one or more embodiments, the disclosed systems utilize detection heads of a neural network to detect digital objects portrayed within a digital image. In some cases, each detection head is associated with one or more digital object classes that are not associated with the other detection heads. Further, in some cases, the detection heads implement multi-scale synchronized batch normalization to normalize feature maps across various feature levels. The disclosed systems further utilize a masking head of the neural network to generate one or more object masks for the detected digital objects. In some cases, the disclosed systems utilize post-processing techniques to filter out low-quality masks.
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Patent Agency Ranking
公开(公告)号：US12271804B2
公开(公告)日：2025-04-08
申请号：US17870496
申请日：2022-07-21
Applicant: Adobe Inc.
Inventor： Mang Tik Chiu , Connelly Barnes , Zijun Wei , Zhe Lin , Yuqian Zhou , Xuaner Zhang , Sohrab Amirghodsi , Florian Kainz , Elya Shechtman
Abstract: Embodiments are disclosed for performing wire segmentation of images using machine learning. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input image, generating, by a first trained neural network model, a global probability map representation of the input image indicating a probability value of each pixel including a representation of wires, and identifying regions of the input image indicated as including the representation of wires. The disclosed systems and methods further comprise, for each region from the identified regions, concatenating the region and information from the global probability map to create a concatenated input, and generating, by a second trained neural network model, a local probability map representation of the region based on the concatenated input, indicating pixels of the region including representations of wires. The disclosed systems and methods further comprise aggregating local probability maps for each region.
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公开(公告)号：US20250086849A1
公开(公告)日：2025-03-13
申请号：US18463333
申请日：2023-09-08
Applicant: ADOBE INC.
Inventor： Yu Zeng , Zhe Lin , Jianming Zhang , Qing Liu , Jason Wen Yong Kuen , John Philip Collomosse
IPC: G06T11/00 , G06F40/295 , G06F40/30 , G06V10/774 , G06V10/776 , G06V20/70
Abstract: Embodiments of the present disclosure include obtaining a text prompt describing an element, layout information indicating a target region for the element, and a precision level corresponding to the element. Some embodiments generate a text feature pyramid based on the text prompt, the layout information, and the precision level, wherein the text feature pyramid comprises a plurality of text feature maps at a plurality of scales, respectively. Then, an image is generated based on the text feature pyramid. In some cases, the image includes an object corresponding to the element of the text prompt at the target region. Additionally, a shape of the object corresponds to a shape of the target region based on the precision level.
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公开(公告)号：US12217395B2
公开(公告)日：2025-02-04
申请号：US17660968
申请日：2022-04-27
Applicant: ADOBE INC.
Inventor： Sangryul Jeon , Zhifei Zhang , Zhe Lin , Scott Cohen , Zhihong Ding
Abstract: Systems and methods for image processing are configured. Embodiments of the present disclosure encode a content image and a style image using a machine learning model to obtain content features and style features, wherein the content image includes a first object having a first appearance attribute and the style image includes a second object having a second appearance attribute; align the content features and the style features to obtain a sparse correspondence map that indicates a correspondence between a sparse set of pixels of the content image and corresponding pixels of the style image; and generate a hybrid image based on the sparse correspondence map, wherein the hybrid image depicts the first object having the second appearance attribute.
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219.发明授权公开(公告)号：US12198224B2
公开(公告)日：2025-01-14
申请号：US17651075
申请日：2022-02-15
Applicant: ADOBE INC.
Inventor： Xin Yuan , Zhe Lin , Jason Wen Yong Kuen , Jianming Zhang , John Philip Collomosse
Abstract: Systems and methods for image generation are described. Embodiments of the present disclosure receive a text phrase that describes a target image to be generated; generate text features based on the text phrase; retrieve a search image based on the text phrase; and generate the target image using an image generation network based on the text features and the search image.
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公开(公告)号：US12169895B2
公开(公告)日：2024-12-17
申请号：US17502782
申请日：2021-10-15
Applicant: Adobe Inc.
Inventor： Yifan Liu , Jianming Zhang , He Zhang , Elya Shechtman , Zhe Lin
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate a height map for a digital object portrayed in a digital image and further utilizes the height map to generate a shadow for the digital object. Indeed, in one or more embodiments, the disclosed systems generate (e.g., utilizing a neural network) a height map that indicates the pixels heights for pixels of a digital object portrayed in a digital image. The disclosed systems utilize the pixel heights, along with lighting information for the digital image, to determine how the pixels of the digital image project to create a shadow for the digital object. Further, in some implementations, the disclosed systems utilize the determined shadow projections to generate (e.g., utilizing another neural network) a soft shadow for the digital object. Accordingly, in some cases, the disclosed systems modify the digital image to include the shadow.
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