公开(公告)号：US10891537B2

公开(公告)日：2021-01-12

申请号：US16359346

申请日：2019-03-20

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Yunhe Wang ,  Chunjing Xu ,  Kai Han

IPC: G06N3/04 ,  G06F17/15 ,  G06F17/16

Abstract: This application discloses a convolutional neural network-based image processing method and image processing apparatus in the artificial intelligence field. The method may include: receiving an input image; preprocessing the input image to obtain preprocessed image information; and performing convolution on the image information using a convolutional neural network, and outputting a convolution result. In embodiments of this application, the image processing apparatus may store primary convolution kernels of convolution layers, and before performing convolution using the convolution layers, generate secondary convolution kernels using the primary convolution kernels of the convolution layers.

公开(公告)号：US09898860B2

公开(公告)日：2018-02-20

申请号：US15088878

申请日：2016-04-01

Applicant: Huawei Technologies Co., Ltd.

Inventor： Jianzhuang Liu ,  Wenqi Ju ,  Chunjing Xu

IPC: G06T17/10 ,  G06T7/00 ,  G06F3/0354 ,  G06T1/20 ,  G06F3/0488 ,  G06T19/20 ,  G06T11/20 ,  G06T17/00 ,  G06T7/543

CPC classification number: G06T17/10 ,  G06F3/03543 ,  G06F3/04883 ,  G06T1/20 ,  G06T7/543 ,  G06T11/206 ,  G06T17/00 ,  G06T19/20

Abstract: A method, an apparatus and a terminal for reconstructing a three-dimensional object, where the method includes acquiring two-dimensional line drawing information, segmenting, according to the two-dimensional line drawing information and according to a degree of freedom, the two-dimensional line drawing to obtain at least one line sub-drawing, where the degree of freedom is a smallest quantity of vertices that need to be known for determining a spatial location of the three-dimensional object that includes planes, reconstructing a three-dimensional sub-object according to the line sub-drawing, and combining all three-dimensional sub-objects to obtain the three-dimensional object, and hence, the three-dimensional object can be automatically reconstructed according to two-dimensional line drawing information.

公开(公告)号：US20160275355A1

公开(公告)日：2016-09-22

申请号：US15167388

申请日：2016-05-27

Applicant: Huawei Technologies Co., Ltd.

Inventor： Limin Wang ,  Yu Qiao ,  Wei Li ,  Chunjing Xu ,  Xiaoou Tang

IPC: G06K9/00 ,  G06F17/30

CPC classification number: G06K9/00718 ,  G06F17/30781 ,  G06F17/30784 ,  G06F17/30811 ,  G06K9/00724 ,  G06K9/00744 ,  G06K9/00758 ,  G06K9/00765 ,  G06K9/6218

Abstract: A video classification method and apparatus relate to the field of electronic and information technologies, so that precision of video classification can be improved. The method includes: segmenting a video in a sample video library according to a time sequence, to obtain a segmentation result, and generating a motion atom set; generating, by using the motion atom set and the segmentation result, a motion phrase set that can indicate a complex motion pattern, and generating a descriptive vector, based on the motion phrase set, of the video in the sample video library; and determining, by using the descriptive vector, a to-be-detected video whose category is the same as that of the video in the sample video library. The method is applicable to a scenario of video classification.

Abstract translation: 视频分类方法和装置涉及电子和信息技术领域，从而可以提高视频分类的精度。 该方法包括：根据时间序列对样本视频库中的视频进行分割，以获得分割结果，并生成运动原子集; 通过使用运动原子集合和分割结果，生成可以指示复杂运动模式的运动短语集合，并且基于运动短语集合生成示例视频库中的视频的描述向量; 以及通过使用描述向量来确定其类别与样本视频库中的视频的类别相同的待检测视频。 该方法适用于视频分类场景。

公开(公告)号：US12243284B2

公开(公告)日：2025-03-04

申请号：US17587689

申请日：2022-01-28

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Kai Han ,  Yunhe Wang ,  Han Shu ,  Chunjing Xu

IPC: G06V10/00 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82

Abstract: This application relates to an image recognition technology in the field of computer vision in the field of artificial intelligence, and provides an image classification method and apparatus. The method includes: obtaining an input feature map of a to-be-processed image; performing convolution processing on the input feature map based on M convolution kernels of a neural network, to obtain a candidate output feature map of M channels, where M is a positive integer; performing matrix transformation on the M channels of the candidate output feature map based on N matrices, to obtain an output feature map of N channels, where a quantity of channels of each of the N matrices is less than M, N is greater than M, and N is a positive integer; and classify the to-be-processed image based on the output feature map, to obtain a classification result of the to-be-processed image.

公开(公告)号：US10402627B2

公开(公告)日：2019-09-03

申请号：US15639220

申请日：2017-06-30

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Wenqi Ju ,  Wei Li ,  Chunjing Xu

IPC: G06K9/00 ,  G06K9/62

Abstract: The present invention provides a method and an apparatus for determining an identity identifier of a face in a face image, and a terminal. The method includes: obtaining an original feature vector of a face image; selecting k candidate vectors from a face image database; selecting a matching vector of the original feature vector from the k candidate vectors; and determining, an identity identifier that is of the matching vector. In embodiments of the present invention, a face image database stores a medium-level feature vector formed by means of mutual interaction between a low-level face feature vector and autocorrelation and cross-correlation submatrices in a joint Bayesian probability matrix. The medium-level feature vector includes information about mutual interaction between the face feature vector and the autocorrelation and cross-correlation submatrices in the joint Bayesian probability matrix, so that efficiency and accuracy of facial recognition can be improved.

公开(公告)号：US20160217610A1

公开(公告)日：2016-07-28

申请号：US15088878

申请日：2016-04-01

Applicant: Huawei Technologies Co., Ltd.

Inventor： Jianzhuang Liu ,  Wenqi Ju ,  Chunjing Xu

IPC: G06T17/10 ,  G06T7/00 ,  G06F3/0354 ,  G06T1/20 ,  G06F3/0488 ,  G06T19/20 ,  G06T11/20

CPC classification number: G06T17/10 ,  G06F3/03543 ,  G06F3/04883 ,  G06T1/20 ,  G06T7/543 ,  G06T11/206 ,  G06T17/00 ,  G06T19/20

Abstract: A method, an apparatus and a terminal for reconstructing a three-dimensional object, where the method includes acquiring two-dimensional line drawing information, segmenting, according to the two-dimensional line drawing information and according to a degree of freedom, the two-dimensional line drawing to obtain at least one line sub-drawing, where the degree of freedom is a smallest quantity of vertices that need to be known for determining a spatial location of the three-dimensional object that includes planes, reconstructing a three-dimensional sub-object according to the line sub-drawing, and combining all three-dimensional sub-objects to obtain the three-dimensional object, and hence, the three-dimensional object can be automatically reconstructed according to two-dimensional line drawing information.

Abstract translation: 一种用于重建三维物体的方法，装置和终端，其中所述方法包括获取二维线条图信息，根据二维线条图信息并根据自由度分割二维线条图， 以获得至少一条线图，其中自由度是确定包括平面的三维物体的空间位置需要知道的最小数量的顶点，重建三维子图 - 对象，并且将所有三维子对象组合以获得三维对象，因此可以根据二维线条图自动重建三维对象。

公开(公告)号：US12254064B2

公开(公告)日：2025-03-18

申请号：US17488735

申请日：2021-09-29

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Hanting Chen ,  Yunhe Wang ,  Chuanjian Liu ,  Kai Han ,  Chunjing Xu

IPC: G06F18/214 ,  G06F18/243 ,  G06N3/047

Abstract: The present application discloses an image generation method, a neural network compression method, and a related apparatus and device in the field of artificial intelligence. The image generation method includes: inputting a first matrix into an initial image generator to obtain a generated image; inputting the generated image into a preset discriminator to obtain a determining result, where the preset discriminator is obtained through training based on a real image and a category corresponding to the real image; updating the initial image generator based on the determining result to obtain a target image generator; and further inputting a second matrix into the target image generator to obtain a sample image. Further, a neural network compression method is disclosed, to compress the preset discriminator based on the sample image obtained by using the foregoing image generation method.

公开(公告)号：US20220327363A1

公开(公告)日：2022-10-13

申请号：US17848081

申请日：2022-06-23

Applicant: Huawei Technologies Co., Ltd.

Inventor： Yixing Xu ,  Yehui Tang ,  Li Qian ,  Yunhe Wang ,  Chunjing Xu

IPC: G06N3/04 ,  G06N3/08

Abstract: A neural network training method in the artificial intelligence field includes: inputting training data into a neural network; determining a first input space of a second target layer in the neural network based on a first output space of a first target layer in the neural network; and inputting a feature vector in the first input space into the second target layer, where a capability of fitting random noise by the neural network when the feature vector in the first input space is input into the second target layer is lower than a capability of fitting the random noise by using an output space that is in the neural network and that exists when a feature vector in the first output space is input into the second target layer. This application helps avoid an overfitting phenomenon that occurs when the neural network processes an image, text, or speech.

公开(公告)号：US10043308B2

公开(公告)日：2018-08-07

申请号：US15296138

申请日：2016-10-18

Applicant: Huawei Technologies Co., Ltd.

Inventor： Wei Zhang ,  Chunjing Xu ,  Jianzhuang Liu

IPC: G06F7/533 ,  G06T17/10 ,  G06T7/12 ,  G06T7/149 ,  G06T17/00 ,  G06T7/13

Abstract: An image processing method and apparatus are disclosed. The method includes obtaining a two-dimensional target face image, receiving an identification curve marked by a user in the target face image, locating a facial contour curve of a face from the target face image according to the identification curve and by using an image segmentation technology, determining a three-dimensional posture and a feature point position of the face in the target face image, and constructing a three-dimensional shape of the face in the target face image according to the facial contour curve, the three-dimensional posture, and the feature point position of the face in the target face image by using a preset empirical model of a three-dimensional face shape and a target function matching the empirical model of the three-dimensional face shape.

公开(公告)号：US09514356B2

公开(公告)日：2016-12-06

申请号：US14841928

申请日：2015-09-01

Applicant: Huawei Technologies Co., Ltd.

Inventor： Chaochao Lu ,  Chunjing Xu ,  Xiaoou Tang

IPC: G06K9/62 ,  G06K9/00

CPC classification number: G06K9/00288 ,  G06K9/00268 ,  G06K9/6232

Abstract: A method and an apparatus for generating a facial feature verification model. The method includes acquiring N input facial images, performing feature extraction on the N input facial images, to obtain an original feature representation of each facial image, and forming a face sample library, for samples of each person with an independent identity, obtaining an intrinsic representation of each group of face samples in at least two groups of face samples, training a training sample set of the intrinsic representation, to obtain a Bayesian model of the intrinsic representation, and obtaining a facial feature verification model according to a preset model mapping relationship and the Bayesian model of the intrinsic representation. In the method and apparatus for generating a facial feature verification model in the embodiments of the present disclosure, complexity is low and a calculation amount is small.

Abstract translation: 一种用于生成面部特征验证模型的方法和装置。 该方法包括获取N个输入的面部图像，对N个输入的面部图像执行特征提取，以获得每个面部图像的原始特征表示，以及形成一个具有独立身份的每个人的样本的面部样本库， 在至少两组面部样本中对每组面部样本的表示，训练内在表示的训练样本集合，以获得内在表示的贝叶斯模型，并且根据预设模型映射关系获得面部特征验证模型 和贝叶斯模型的内在表征。 在本公开的实施例中用于生成面部特征验证模型的方法和装置中，复杂度低，计算量小。