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公开(公告)号：US20200057883A1
公开(公告)日：2020-02-20
申请号：US16665060
申请日：2019-10-28
Inventor： Yanhao Ge , Jilin Li , Chengjie Wang
Abstract: A face attribute recognition method, electronic device, and storage medium. The method may include obtaining a face image, inputting the face image into an attribute recognition model, performing a forward calculation on the face image using the attribute recognition model to obtain a plurality of attribute values according to different types of attributes, and outputting the plurality of attribute values, the plurality of attribute values indicating recognition results of a plurality of attributes of the face image. The attribute recognition model may be obtained through training based on a plurality of sample face images, a plurality of sample attribute recognition results of the plurality of sample face images, and the different types of attributes.
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2.发明授权公开(公告)号：US12154380B2
公开(公告)日：2024-11-26
申请号：US17969435
申请日：2022-10-19
Inventor： Yun Cao , Hui Ni , Feida Zhu , Xiaozhong Ji , Ying Tai , Yanhao Ge , Chengjie Wang
IPC: G06V40/16 , G06T15/04 , G06T19/20 , G06V10/774 , G06V20/70
Abstract: A face image processing method and apparatus, a face image display method and apparatus, and a device are provided, belonging to the technical field of image processing. The method includes: acquiring a first face image of a person; invoking an age change model to predict a texture difference map of the first face image at a specified age, the texture difference map being used for reflecting a texture difference between a face texture in the first face image and a face texture of a second face image of the person at the specified age; and performing image processing on the first face image based on the texture difference map to obtain the second face image.
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3.发明授权公开(公告)号：US11915514B2
公开(公告)日：2024-02-27
申请号：US17184368
申请日：2021-02-24
Inventor： Xuan Cao , Weijian Cao , Yanhao Ge , Chengjie Wang
IPC: G06T7/00 , G06V40/16 , G06V10/764 , G06V10/82
CPC classification number: G06V40/165 , G06V10/764 , G06V10/82 , G06V40/161 , G06V40/171
Abstract: This application relates to a method and an apparatus for detecting facial key points, a computer device, and a storage medium including: acquiring a to-be-detected face image from a current frame; determining partial images in the to-be-detected face image, each partial image including one or more facial key points; determining, within each of the partial images, candidate points of the one or more facial key points corresponding to the partial image, respectively; and jointly constraining the candidate points in the partial images to determine a set of facial key points from the candidate points for the to-be-detected face image. For the partial images in the entire to-be-detected face image, the candidate points of the facial key points corresponding to the partial images are respectively determined. Therefore, a calculation amount may be reduced, and the efficiency of determining the candidate points of the facial key points is improved.
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公开(公告)号：US12293480B2
公开(公告)日：2025-05-06
申请号：US17976259
申请日：2022-10-28
Inventor： Yandan Zhao , Shuheng Lin , Xuan Cao , Yanhao Ge , Chengjie Wang , Weijan Cao
Abstract: This application provides a method for reconstructing a three-dimensional model, a method for training a three-dimensional reconstruction model, an apparatus, a computer device, and a storage medium. The method for reconstructing a three-dimensional model includes: obtaining an image feature coefficient of an input image; respectively obtaining, according to the image feature coefficient, a global feature map and an initial local feature map based on a texture and a shape of the input image; performing edge smoothing on the initial local feature map, to obtain a target local feature map; respectively splicing the global feature map and the target local feature map based on the texture and the shape, to obtain a target texture image and a target shape image; and performing three-dimensional model reconstruction according to the target texture image and the target shape image, to obtain a target three-dimensional model.
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公开(公告)号：US11436739B2
公开(公告)日：2022-09-06
申请号：US16922196
申请日：2020-07-07
Inventor： Yabiao Wang , Yanhao Ge , Zhenye Gan , Yuan Huang , Changyou Deng , Yafeng Zhao , Feiyue Huang , Yongjian Wu , Xiaoming Huang , Xiaolong Liang , Chengjie Wang , Jilin Li
Abstract: This present disclosure describes a video image processing method and apparatus, a computer-readable medium and an electronic device, relating to the field of image processing technologies. The method includes determining, by a device, a target-object region in a current frame in a video. The device includes a memory storing instructions and a processor in communication with the memory. The method also includes determining, by the device, a target-object tracking image in a next frame and corresponding to the target-object region; and sequentially performing, by the device, a plurality of sets of convolution processing on the target-object tracking image to determine a target-object region in the next frame. A quantity of convolutions of a first set of convolution processing in the plurality of sets of convolution processing is less than a quantity of convolutions of any other set of convolution processing.
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Patent Agency Ranking
公开(公告)号：US11275932B2
公开(公告)日：2022-03-15
申请号：US16938858
申请日：2020-07-24
Inventor： Siqian Yang , Jilin Li , Yongjian Wu , Yichao Yan , Keke He , Yanhao Ge , Feiyue Huang , Chengjie Wang
Abstract: This application discloses a human attribute recognition method performed at a computing device. The method includes: determining a human body region image in a surveillance image; inputting the human body region image into a multi-attribute convolutional neural network model, to obtain, for each of a plurality of human attributes in the human body region image, a probability that the human attribute corresponds to a respective predefined attribute value, the multi-attribute convolutional neural network model being obtained by performing multi-attribute recognition and training on a set of pre-obtained training images by using a multi-attribute convolutional neural network; determining, for each of the plurality of human attributes in the human body region image, the attribute value of the human attribute based on the corresponding probability; and displaying the attribute values of the plurality of human attributes next to the human body region image.
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公开(公告)号：US11200404B2
公开(公告)日：2021-12-14
申请号：US17089435
申请日：2020-11-04
Inventor： Yandan Zhao , Yichao Yan , Weijian Cao , Yun Cao , Yanhao Ge , Chengjie Wang , Jilin Li
Abstract: This application relates to feature point positioning technologies. The technologies involve positioning a target area in a current image; determining an image feature difference between a target area in a reference image and the target area in the current image, the reference image being a frame of image that is processed before the current image and that includes the target area; determining a target figure point location of the target area in the reference image; determining a target feature point location difference between the target area in the reference image and the target area in the current image according to a feature point location difference determining model and the image feature difference; and positioning a target feature point in the target area in the current image according to the target feature point location of the target area in the reference image and the target feature point location difference.
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公开(公告)号：US11151360B2
公开(公告)日：2021-10-19
申请号：US16665060
申请日：2019-10-28
Inventor： Yanhao Ge , Jilin Li , Chengjie Wang
Abstract: A face attribute recognition method, electronic device, and storage medium. The method may include obtaining a face image, inputting the face image into an attribute recognition model, performing a forward calculation on the face image using the attribute recognition model to obtain a plurality of attribute values according to different types of attributes, and outputting the plurality of attribute values, the plurality of attribute values indicating recognition results of a plurality of attributes of the face image. The attribute recognition model may be obtained through training based on a plurality of sample face images, a plurality of sample attribute recognition results of the plurality of sample face images, and the different types of attributes.
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公开(公告)号：US11854310B2
公开(公告)日：2023-12-26
申请号：US17580548
申请日：2022-01-20
Inventor： Xuan Cao , Shouhong Ding , Jia Meng , Taiping Yao , Yanhao Ge , Chengjie Wang
CPC classification number: G06V40/45 , G06V10/14 , G06V40/166 , G06V40/168 , G06V40/63
Abstract: A face liveness detection method is performed by an electronic device. The method includes: obtaining an initial face image of an object and a face image set of the object captured at N different illumination directions; obtaining N difference images according to the initial face image and the N face images in the face image set; generating a normal map and an albedo map according to the N difference images and the N illumination directions; and determining a face liveness detection result according to the N difference images, the normal map, and the albedo map, the face liveness detection result indicating whether the object has a live face or not. In this application, three-dimensional (3D) geometric information and surface material information of a face image are considered, thereby recognizing the authenticity of the face image, and effectively resisting different face liveness attack manners.
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10.发明授权公开(公告)号：US11710335B2
公开(公告)日：2023-07-25
申请号：US17504682
申请日：2021-10-19
Inventor： Keke He , Jing Liu , Yanhao Ge , Chengjie Wang , Jilin Li
CPC classification number: G06V40/103 , G06F18/217 , G06F18/25 , G06V10/40 , G06V10/98
Abstract: The present disclosure describes human body attribute recognition methods and apparatus, electronic devices, and a storage medium. The method includes acquiring a sample image containing a plurality of to-be-detected areas being labeled with true values of human body attributes; generating, through a recognition model, a heat map of the sample image and heat maps of the to-be-detected areas to obtain a global heat map and local heat maps; fusing the global and the local heat maps to obtain a fused image, and performing human body attribute recognition on the fused image to obtain predicted values; determining a focus area of each type of human body attribute according to the global and the local heat maps; correcting the recognition model by using the focus area, the true values, and the predicted values; and performing, based on the corrected recognition model, human body attribute recognition on a to-be-recognized image.
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