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公开(公告)号：US20210406579A1
公开(公告)日：2021-12-30
申请号：US17468848
申请日：2021-09-08
Inventor： Tianwei Lin , Dongliang He , Fu Li
Abstract: The present disclosure provides a model training method, an identification method, device, storage medium and program product, relating to computer vision technology and deep learning technology. In the solution provided by the present application, the image is deformed by the means of deforming the first training image without label itself, and the first unsupervised identification result is obtained by using the first model to identify the image before deformation, and the second unsupervised identification result is obtained by using the second model to identify the image after deformation, and the first unsupervised identification result of the first model is deformed, thus a consistency loss function can be constructed according to the second unsupervised identification result and the scrambled identification result. In this way, it is able to enhance the constraint effect of the consistency loss function and avoid destroying the scene semantic information of the images used for training.
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Patent Agency Ranking
公开(公告)号：US20230036338A1
公开(公告)日：2023-02-02
申请号：US17963384
申请日：2022-10-11
Inventor： Fanglong Liu , Xin Li , Dongliang He
Abstract: A method and apparatus for generating an image restoration model, a medium and a program product are provided. The method includes: obtaining a first image and a second image, wherein the second image is an image obtained by restoring the first image; synthesizing images corresponding to feature points of the first image and the first image to obtain a synthesized image; and performing training by using the second image and the synthesized image to obtain an image restoration model.
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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：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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5.发明公开公开(公告)号：US20230232116A1
公开(公告)日：2023-07-20
申请号：US18156187
申请日：2023-01-18
Inventor： Qi Zhang , Dongliang He , Xin Li
IPC: H04N23/741 , G06T3/40 , G06T5/00 , G06T5/50
CPC classification number: H04N23/741 , G06T3/40 , G06T5/007 , G06T5/50 , G06T2207/20081 , G06T2207/20208 , G06T2207/20221
Abstract: Provided are a video conversion method, an electronic device and a non-transitory computer readable storage medium. The implementation scheme is as follows: a to-be-converted SDR video is acquired; one frame is extracted from the to-be-converted SDR video to serve as a current SDR image, the current SDR image is input into a parameter predictor and a generator, and an adjustment parameter corresponding to the current SDR image is output from the parameter predictor; the adjustment parameter corresponding to the current SDR image is input into the generator, and an HDR image corresponding to the current SDR image is output from the generator; and the operation described above is repeatedly performed until frames are converted into HDR images each of which corresponds to a respective frame of the frames; and a corresponding HDR video is generated based on the HDR images corresponding to the frames.
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公开(公告)号：US20230230205A1
公开(公告)日：2023-07-20
申请号：US18155901
申请日：2023-01-18
Inventor： Xin Li , Dongliang He , Qi Zhang
CPC classification number: G06T5/001 , G06T3/40 , G06T2207/20081 , G06T2207/20084 , G06T2207/20016 , G06T2207/10024
Abstract: Provided are an image enhancement method and apparatus, an electronic device, and a storage medium. The image enhancement method includes: acquiring an original image, and configuring the original image as a current image; selecting a renderer from a plurality of pre-trained renderers as a current renderer in response to the current image satisfying a preset enhancement condition; and inputting the current image to the current renderer, and outputting, through the current renderer, an enhanced image of the current image in a dimension corresponding to the current renderer; and repeating the preceding operation by configuring the enhanced image of the current image in the dimension corresponding to the current renderer as the current image until the current image does not satisfy the enhancement condition.
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