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公开(公告)号：US20220391587A1
公开(公告)日：2022-12-08
申请号：US17889074
申请日：2022-08-16
Inventor： Yuan Feng , Xiang Long , Honghui Zheng , Ying Xin , Bin Zhang , Chao Li , Xiaodi Wang , Yi Gu , Yunhao Wang , Yan Peng , Zhuang Jia , Shumin Han
IPC: G06F40/279 , G06V10/40 , G06F40/58 , G06F16/532 , G06F16/583
Abstract: A method of training an image-text retrieval model, a method of multimodal image retrieval, an electronic device and a storage medium, each relating to the technical field of artificial intelligence, and in particular, to fields of computer vision and deep learning technologies. Sample data including a sample text and a sample image is acquired. The sample text includes a sample text in a first language and a sample text in a second language. The sample text in the first language and the sample text in the second language are processed by using the text encoding sub-model to obtain a sample text feature of the sample data. The sample image is processed by using the image encoding sub-model to obtain a sample image feature of the sample data. The image-text retrieval model is trained according to the sample text feature and the sample image feature.
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公开(公告)号：US20230154163A1
公开(公告)日：2023-05-18
申请号：US18151108
申请日：2023-01-06
Inventor： Zhuang Jia , Xiang Long , Yan Peng , Honghui Zheng , Bin Zhang , Yunhao Wang , Ying Xin , Chao Li , Xiaodi Wang , Song Xue , Yuan Feng , Shumin Han
IPC: G06V10/774 , G06V10/58 , G06V10/764 , G06V10/776 , G06V20/70 , G06V10/77
CPC classification number: G06V10/774 , G06V10/58 , G06V10/764 , G06V10/776 , G06V20/70 , G06V10/7715
Abstract: A method for recognizing a category of an image includes: acquiring a spectral image; training an image recognition model based on the spectral image, in which the image recognition model acquires a spectral semantic feature of each pixel, a minimum distance between each pixel and each category, and a spectral distance between a first spectrum of each pixel and a second spectrum of each category; splices them; and performs classification and recognition based on the spliced feature to output a recognition probability of each pixel under each category; determining a loss function of the image recognition model, adjusting the image recognition model based on the loss function, and returning to training the adjusted image recognition model based on the spectral image until training ends; recognizing a maximum recognition probability, output from a target image recognition model, and using a category corresponding to the maximum recognition probability as a target category.
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Patent Agency Ranking
公开(公告)号：US11641446B2
公开(公告)日：2023-05-02
申请号：US17643687
申请日：2021-12-10
Inventor： Chao Li
Abstract: The disclosure discloses a method for video frame interpolation. The method includes: obtaining a first visual semantic feature and first pixel information of a first frame, and obtaining a second visual semantic feature and second pixel information of a second frame; generating semantic optical flow information based on the first visual semantic feature and the second visual semantic feature; generating pixel optical flow information based on the first pixel information and the second pixel information; and generating an interpolation frame between the first frame and the second frame based on the semantic optical flow information and the pixel optical flow information, and interpolating the interpolation frame between the first frame and the second frame.
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公开(公告)号：US20240249555A1
公开(公告)日：2024-07-25
申请号：US17995743
申请日：2022-04-20
Inventor： Song Xue , Yuan Feng , Ying Xin , Bin Zhang , Chao Li , Xiaodi Wang , Yunhao Wang , Yi Gu , Xiang Long , Honghui Zheng , Yan Peng , Zhuang Jia , Shumin Han
CPC classification number: G06V40/20 , G06T7/73 , G06V10/25 , G06T2207/30196
Abstract: A method for detecting a human behavior includes: obtaining an image to be detected; obtaining a plurality of key points and a plurality of pieces of position information respectively corresponding to the plurality of key points by key-point recognition on the image to be detected; grouping the plurality of key points based on the plurality of pieces of position information to obtain a plurality of key-point groups, the plurality of key-point groups at least including a part of the plurality of key points; and determining a target human behavior based on key points in the plurality of key-point groups.
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公开(公告)号：US20240037911A1
公开(公告)日：2024-02-01
申请号：US18109522
申请日：2023-02-14
Inventor： Ying Xin , Song Xue , Yuan Feng , Chao Li , Bin Zhang , Yunhao Wang , Shumin Han
IPC: G06V10/764 , G06V10/44 , G06V10/80 , G06V10/82
CPC classification number: G06V10/764 , G06V10/44 , G06V10/806 , G06V10/82
Abstract: Provided is an image classification method, an electronic device and a storage medium, relating to a field of artificial intelligence technology, and specifically, to the technical fields of deep learning, image processing and computer vision, which may be applied to scenes such as image classification. The image classification method includes: extracting a first image feature of a target image by using a first network model, where the first network model includes a convolutional neural network module; extracting a second image feature of the target image by using a second network model, where the second network model includes a deep self-attention transformer network (Transformer) module; fusing the first image feature and the second image feature to obtain a target feature to be recognized; and classifying the target image based on the target feature to be recognized.
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6.发明公开公开(公告)号：US20230153387A1
公开(公告)日：2023-05-18
申请号：US18150964
申请日：2023-01-06
Inventor： Chao Li , Ying Xin , Yuan Feng , Bin Zhang , Yunhao Wang , Xiaodi Wang , Yi Gu , Xiang Long , Yan Peng , Honghui Zheng , Zhuang Jia , Shumin Han
IPC: G06F18/214 , G06V10/25
CPC classification number: G06F18/214 , G06V10/25
Abstract: A training method for a human body attribute detection model includes: acquiring positive sample sub-images and negative sample sub-images respectively corresponding to a plurality of human body attribute categories; determining a plurality of first annotation attributes respectively corresponding to the plurality of positive sample sub-images; and a plurality of second annotation attributes respectively corresponding to the plurality of negative sample sub-images; and training an artificial intelligence model according to the plurality of positive sample sub-images, the plurality of negative sample sub-images, the plurality of first annotation attributes and the plurality of second annotation attributes to obtain the human body attribute detection model, so that the human body attribute detection model obtained by training can effectively model fine-grained attributes of the human body.
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公开(公告)号：US20220103782A1
公开(公告)日：2022-03-31
申请号：US17643687
申请日：2021-12-10
Inventor： Chao Li
Abstract: The disclosure discloses a method for video frame interpolation. The method includes: obtaining a first visual semantic feature and first pixel information of a first frame, and obtaining a second visual semantic feature and second pixel information of a second frame; generating semantic optical flow information based on the first visual semantic feature and the second visual semantic feature; generating pixel optical flow information based on the first pixel information and the second pixel information; and generating an interpolation frame between the first frame and the second frame based on the semantic optical flow information and the pixel optical flow information, and interpolating the interpolation frame between the first frame and the second frame.
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