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Patent Agency Ranking
公开(公告)号：US20240320873A1
公开(公告)日：2024-09-26
申请号：US18439036
申请日：2024-02-12
Applicant: ADOBE INC.
Inventor： Tobias Hinz , Ali Aminian , Hao Tan , Kushal Kafle , Oliver Wang , Jingwan Lu
IPC: G06T11/00
CPC classification number: G06T11/00 , G06T2211/441
Abstract: A method, apparatus, non-transitory computer readable medium, and system for image generation include obtaining a text prompt and encoding, using a text encoder jointly trained with an image generation model, the text prompt to obtain a text embedding. Some embodiments generate, using the image generation model, a synthetic image based on the text embedding.
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公开(公告)号：US20210232850A1
公开(公告)日：2021-07-29
申请号：US16750478
申请日：2020-01-23
Applicant: Adobe Inc.
Inventor： Trung Huu Bui , Zhe Lin , Hao Tan , Franck Dernoncourt , Mohit Bansal
Abstract: In implementations of generating descriptions of image relationships, a computing device implements a description system which receives a source digital image and a target digital image. The description system generates a source feature sequence from the source digital image and a target feature sequence from the target digital image. A visual relationship between the source digital image and the target digital image is determined by using cross-attention between the source feature sequence and the target feature sequence. The system generates a description of a visual transformation between the source digital image and the target digital image based on the visual relationship.
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公开(公告)号：US20250104349A1
公开(公告)日：2025-03-27
申请号：US18894176
申请日：2024-09-24
Applicant: ADOBE INC.
Inventor： Sai Bi , Jiahao Li , Hao Tan , Kai Zhang , Zexiang Xu , Fujun Luan , Yinghao Xu , Yicong Hong , Kalyan K. Sunkavalli
Abstract: A method, apparatus, non-transitory computer readable medium, and system for 3D model generation include obtaining a plurality of input images depicting an object and a set of 3D position embeddings, where each of the plurality of input images depicts the object from a different perspective, encoding the plurality of input images to obtain a plurality of 2D features corresponding to the plurality of input images, respectively, generating 3D features based on the plurality of 2D features and the set of 3D position embeddings, and generating a 3D model of the object based on the 3D features.
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4.发明申请公开(公告)号：US20250022459A1
公开(公告)日：2025-01-16
申请号：US18220910
申请日：2023-07-12
Applicant: Adobe Inc.
Inventor： Viet Dac Lai , Trung Bui , Seunghyun Yoon , Quan Tran , Hao Tan , Hanieh Deilamsalehy , Abel Salinas , Franck Dernoncourt
IPC: G10L15/183 , G10L15/065
Abstract: The disclosed method generates helpful training data for a language model, for example, a model implementing a punctuation restoration task, for real-world ASR texts. The method uses a reinforcement learning method using a generative AI model to generate additional data to train the language model. The method allows the generative AI model to learn from real-world ASR text to generate more effective training examples based on gradient feedback from the language model.
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公开(公告)号：US11195048B2
公开(公告)日：2021-12-07
申请号：US16750478
申请日：2020-01-23
Applicant: Adobe Inc.
Inventor： Trung Huu Bui , Zhe Lin , Hao Tan , Franck Dernoncourt , Mohit Bansal
Abstract: In implementations of generating descriptions of image relationships, a computing device implements a description system which receives a source digital image and a target digital image. The description system generates a source feature sequence from the source digital image and a target feature sequence from the target digital image. A visual relationship between the source digital image and the target digital image is determined by using cross-attention between the source feature sequence and the target feature sequence. The system generates a description of a visual transformation between the source digital image and the target digital image based on the visual relationship.
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