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公开(公告)号：US20210192194A1
公开(公告)日：2021-06-24
申请号：US17022219
申请日：2020-09-16
Inventor： Zhizhen Chi , Fu Li , Hao Sun , Dongliang He , Xiang Long , Zhichao Zhou , Ping Wang , Shilei Wen , Errui Ding
Abstract: The present application discloses a video-based human behavior recognition method, apparatus, device and storage medium, and relates to the technical field of human recognitions. The specific implementation scheme lies in: acquiring a human rectangle of each video frame of the video to be recognized, where each human rectangle includes a plurality of human key points, and each of the human key points has a key point feature; constructing a feature matrix according to the human rectangle of the each video frame; convolving the feature matrix with respect to a video frame quantity dimension to obtain a first convolution result and convolving the feature matrix with respect to a key point quantity dimension to obtain a second convolution result; inputting the first convolution result and the second convolution result into a preset classification model to obtain a human behavior category of the video to be recognized.
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公开(公告)号：US20230215132A1
公开(公告)日：2023-07-06
申请号：US18183439
申请日：2023-03-14
CPC classification number: G06V10/60 , G06T3/40 , G06T5/50 , G06V10/44 , G06V10/62 , G06V10/761 , G06T2207/20221
Abstract: A method for generating a relighted image includes: obtaining a to-be-processed image and a guidance image corresponding to the to-be-processed image; obtaining a first intermediate image consistent with an illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a time domain based on the guidance image; obtaining a second intermediate image consistent with the illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a frequency domain based on the guidance image; and obtaining a target relighted image corresponding to the to-be-processed image based on the first intermediate image and the second intermediate image.
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Patent Agency Ranking
公开(公告)号：US20230047628A1
公开(公告)日：2023-02-16
申请号：US17976668
申请日：2022-10-28
Inventor： Desen ZHOU , Jian Wang , Hao Sun
Abstract: A human-object interaction detection method, a neural network and a training method therefor is provided. The human-object interaction detection method includes: performing first target feature extraction on image features of an image to obtain first target features; performing first interaction feature extraction on image features to obtain first interaction features and scores thereof; determining at least some first interaction features in the first interaction features based on the score of each of the first interaction features; determining first motion features based on the at least some first interaction features and the image features; processing the first target features to obtain target information of targets in the image; processing the first motion features to obtain motion information of one or more motions in the image; and matching the targets with the motions to obtain a human-object interaction detection result.
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公开(公告)号：US11430265B2
公开(公告)日：2022-08-30
申请号：US17022219
申请日：2020-09-16
Inventor： Zhizhen Chi , Fu Li , Hao Sun , Dongliang He , Xiang Long , Zhichao Zhou , Ping Wang , Shilei Wen , Errui Ding
Abstract: The present application discloses a video-based human behavior recognition method, apparatus, device and storage medium, and relates to the technical field of human recognitions. The specific implementation scheme lies in: acquiring a human rectangle of each video frame of the video to be recognized, where each human rectangle includes a plurality of human key points, and each of the human key points has a key point feature; constructing a feature matrix according to the human rectangle of the each video frame; convolving the feature matrix with respect to a video frame quantity dimension to obtain a first convolution result and convolving the feature matrix with respect to a key point quantity dimension to obtain a second convolution result; inputting the first convolution result and the second convolution result into a preset classification model to obtain a human behavior category of the video to be recognized.
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公开(公告)号：US20220230343A1
公开(公告)日：2022-07-21
申请号：US17709291
申请日：2022-03-30
Inventor： Xiaoqing Ye , Xiao Tan , Hao Sun
IPC: G06T7/593
Abstract: A computer-implemented stereo matching method includes: obtaining a first binocular image; inputting the first binocular image into an object model for a first operation to obtain a first initial disparity map and a first offset disparity map with respect to the first initial disparity map; and performing aggregation on the first initial disparity map and the first offset disparity map to obtain a first target disparity map of the first binocular image. The first initial disparity map is obtained through stereo matching on a second binocular image corresponding to the first binocular image, a size of the second binocular image is smaller than a size of the first binocular image, and the first offset disparity map is obtained through stereo matching on the first binocular image within a predetermined disparity offset range.
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公开(公告)号：US11288887B2
公开(公告)日：2022-03-29
申请号：US16869411
申请日：2020-05-07
Inventor： Xipeng Yang , Xiao Tan , Hao Sun , Shilei Wen , Errui Ding
Abstract: Embodiments of the present disclosure provide an object tracking method and an apparatus. The method includes: obtaining multiple frames of first images shot by a first camera apparatus and a first shooting moment of each frame of the first images, where the first images include a first object; obtaining multiple frames of second images shot by a second camera apparatus and a second shooting moment of each frame of the second images, where the second images include a second object; obtaining a distance between the first camera apparatus and the second camera apparatus; and judging whether the first object and the second object are the same object according to the multiple frames of the first images, the first shooting moment of each frame of the first images, the multiple frames of the second images, the second shooting moment of each frame of the second images and the distance.
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公开(公告)号：US20220092353A1
公开(公告)日：2022-03-24
申请号：US17540207
申请日：2021-12-01
Inventor： Ruixue Liu , Xiameng Qin , Mengyi En , Kun Yao , Chengquan Zhang , Shengxian Zhu , Yunhao Li , Junyu Han , Hao Sun
Abstract: A computer-implemented method includes: acquiring training data, the training data includes training images for a preset vertical type, and the training images include a first training image containing real data of the preset vertical type and a second training image containing virtual data of the preset vertical type ; building a basic model, the basic model includes a deep learning network, and the deep learning network is configured to recognize the training images to extract text data in the training image; and training the basic model by using the training data to obtain the image recognition model.
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