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公开(公告)号：US12100192B2
公开(公告)日：2024-09-24
申请号：US17374810
申请日：2021-07-13
发明人： Dongdong Bai , Yonggen Ling , Wei Liu
IPC分类号： G06V10/44 , G06F18/214 , G06N3/08 , G06V10/77 , G06V10/774 , G06V10/82
CPC分类号： G06V10/454 , G06F18/2148 , G06N3/08 , G06V10/7715 , G06V10/7747 , G06V10/82
摘要： A computer device extracts local features of sample images based on a first part of a convolutional neural network (CNN) model. The sample images comprise a plurality of images taken at the same place. The device; aggregates the local features into feature vectors having a first dimensionality based on a second part of the CNN model. The device obtains compressed representation vectors of the feature vectors based on a third part of the CNN model. The compressed representation vectors have a second dimensionality less than the first dimensionality. The device trains the CNN model, and obtains a trained CNN mode satisfying a preset condition in accordance with the training.
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公开(公告)号：US12099577B2
公开(公告)日：2024-09-24
申请号：US17520612
申请日：2021-11-05
发明人： Lingxue Song , Dihong Gong , Zhifeng Li , Wei Liu
IPC分类号： G06F18/2413 , G06F16/53 , G06F16/583 , G06F18/21 , G06F18/214 , G06F18/22 , G06F18/25 , G06F18/28 , G06N3/08 , G06V10/28 , G06V10/50 , G06V10/75 , G06V40/16
CPC分类号： G06F18/2413 , G06F16/53 , G06F16/5854 , G06F18/214 , G06F18/2163 , G06F18/22 , G06F18/25 , G06F18/28 , G06N3/08 , G06V10/28 , G06V10/50 , G06V10/757 , G06V10/759 , G06V40/172
摘要： An object recognition method is provided. The method includes: detecting an occlusion region of an object in an image, to obtain a binary image; obtaining occlusion binary image blocks; querying a mapping relationship between occlusion binary image blocks and binary masks included in a binary mask dictionary to obtain binary masks corresponding to the occlusion binary image blocks; synthesizing the binary masks queried based on each of the occlusion binary image blocks, to obtain a binary mask corresponding to the binary image; and determining a matching relationship between the image and a prestored object image, based on the binary mask corresponding to the binary image, a feature of the prestored object image, and a feature of the to-be-recognized image.
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公开(公告)号：US12087069B2
公开(公告)日：2024-09-10
申请号：US17516585
申请日：2021-11-01
发明人： Wanchao Chi , Chong Zhang , Yonggen Ling , Wei Liu , Zhengyou Zhang , Zejian Yuan , Ziyang Song , Ziyi Yin
IPC分类号： G06K9/00 , G06N3/045 , G06V30/242 , G06V40/20
CPC分类号： G06V30/242 , G06N3/045 , G06V40/20
摘要： An artificial intelligence-based action recognition method includes: determining, according to video data comprising an interactive object, node sequence information corresponding to video frames in the video data, the node sequence information of each video frame including position information of nodes in a node sequence, the nodes in the node sequence being nodes of the interactive object that are moved to implement a corresponding interactive action; determining action categories corresponding to the video frames in the video data, including: determining, according to the node sequence information corresponding to N consecutive video frames in the video data, action categories respectively corresponding to the N consecutive video frames; and determining, according to the action categories corresponding to the video frames in the video data, a target interactive action made by the interactive object in the video data.
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公开(公告)号：US12067690B2
公开(公告)日：2024-08-20
申请号：US17497883
申请日：2021-10-08
发明人： Tianyu Sun , Haozhi Huang , Wei Liu
CPC分类号： G06T3/04 , G06F18/214 , G06N3/045 , G06N3/088 , G06T9/00 , G06V10/95 , G06V40/168 , G06V40/174
摘要： An image processing method is provided. The method includes: encoding an input image based on an attention mechanism to obtain an encoding tensor set and an attention map set of the input image; obtaining an encoding result of the input image according to the encoding tensor set and the attention map set, the encoding result of the input image recording an identity feature of a human face in the input image; encoding an expression image to obtain an encoding result of the expression image, the encoding result of the expression image recording an expression feature of a human face in the expression image; and generating an output image according to the encoding result of the input image and the encoding result of the expression image, the output image having the identity feature of the input image and the expression feature of the expression image.
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公开(公告)号：US12039454B2
公开(公告)日：2024-07-16
申请号：US17182024
申请日：2021-02-22
发明人： Kaihao Zhang , Wenhan Luo , Lin Ma , Wei Liu
CPC分类号： G06N3/088 , G06N3/04 , G06T7/13 , G06V10/764 , G06V10/82 , G06V20/20 , G06V40/165 , G06V40/169 , G06V40/174 , G06V40/176
摘要： Embodiments of this application disclose a microexpression-based image recognition method and apparatus, and a related device. The method includes: obtaining an original expression image belonging to a first expression type, and inputting the original expression image into an image augmentation model; the original expression image belonging to the first expression type being an image including a microexpression; the image augmentation model being obtained by training with a sample expression image belonging to the first expression type and a sample expression images belonging to a second expression type; augmenting, in the image augmentation model, an expression feature of the microexpression in the original expression image to obtain a target expression image belonging to the second expression type; recognizing an expression attribute type corresponding to the target expression image, and determining the expression attribute type corresponding to the target expression image as an expression attribute type corresponding to the original expression image.
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公开(公告)号：US12026977B2
公开(公告)日：2024-07-02
申请号：US18337802
申请日：2023-06-20
发明人： Hao Wang , Di Hong Gong , Zhi Feng Li , Wei Liu
CPC分类号： G06V40/172 , G06F18/214 , G06F18/217 , G06F18/22 , G06N3/04 , G06N3/08 , G06V40/168 , G06V40/178
摘要： A face recognition method includes: extracting a first identity feature of a first face image by using a feature extraction module, and extracting a second identity feature of a second face image by using the feature extraction module, wherein the feature extraction module is implemented by using a neural network, and pre-trained in a manner such that a correlation coefficient of training batch data is obtained based on an identity feature and an age feature of a sample face image in the training batch data, and decorrelated training of the identity feature and the age feature is performed on the feature extraction module based on the correlation coefficient; and performing a face recognition based on determining a similarity between faces in the first face image and the second face image according to the first identity feature and the second identity feature.
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7.发明授权公开(公告)号：US11915447B2
公开(公告)日：2024-02-27
申请号：US17377316
申请日：2021-07-15
摘要： An audio acquisition device positioning method is provided. In the method, a first image that includes an audio acquisition device is obtained. The audio acquisition device in the first image is identified. First coordinate data of the identified audio acquisition device in the first image is obtained. First displacement data is determined according to the first coordinate data and historical coordinate data of the audio acquisition device. First coordinates of the audio acquisition device are determined according to the first displacement data.
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公开(公告)号：US20230343071A1
公开(公告)日：2023-10-26
申请号：US18333363
申请日：2023-06-12
发明人： Wenhan LUO , Yaodong Wang , Wei Liu
CPC分类号： G06V10/764 , G06V40/168 , G06V40/172 , G06V10/82 , G06V20/52 , G06V40/165 , G06V40/193 , G06V40/40
摘要： In a method for liveness detection, a plurality of images of a user is received. A plurality of facial feature points of the user in the plurality of images is obtained. For each of the plurality of images of the user, facial feature information of a facial feature of the user is determined based on positions of the plurality of facial feature points. An action is determined to be performed by the user based on changes in the facial feature information corresponding to the plurality of images. The user captured in the plurality of images is determined as a live user based on the action being determined as performed by the user.
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9.发明公开公开(公告)号：US20230334905A1
公开(公告)日：2023-10-19
申请号：US18337802
申请日：2023-06-20
发明人： Hao WANG , Di Hong Gong , Zhi Feng Li , Wei Liu
CPC分类号： G06V40/172 , G06N3/04 , G06N3/08 , G06V40/168 , G06F18/22 , G06F18/214 , G06F18/217 , G06V40/178
摘要： A face recognition method includes: extracting a first identity feature of a first face image by using a feature extraction module, and extracting a second identity feature of a second face image by using the feature extraction module, wherein the feature extraction module is implemented by using a neural network, and pre-trained in a manner such that a correlation coefficient of training batch data is obtained based on an identity feature and an age feature of a sample face image in the training batch data, and decorrelated training of the identity feature and the age feature is performed on the feature extraction module based on the correlation coefficient; and performing a face recognition based on determining a similarity between faces in the first face image and the second face image according to the first identity feature and the second identity feature.
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公开(公告)号：US11715224B2
公开(公告)日：2023-08-01
申请号：US17242415
申请日：2021-04-28
发明人： Yuan Gao , Xiang Kai Lin , Lin Chao Bao , Wei Liu
CPC分类号： G06T7/55 , G06T7/337 , G06V10/25 , G06V10/76 , G06V10/803 , G06V10/82 , G06V20/653 , G06V40/162 , G06V40/164 , G06V40/169 , G06V40/171 , G06T2207/10028
摘要： A three-dimensional object reconstruction method, applied to a terminal device or a server, is provided. The method includes obtaining a plurality of video frames of an object; determining three-dimensional location information of key points of the object in the plurality of video frames and physical meaning information of the key points, the physical meaning information indicating respective positions of the object; determining a correspondence between the key points having the same physical meaning information in the plurality of video frames; and generating a three-dimensional object according to the correspondence and the three-dimensional location information of the key points.
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