公开(公告)号：US20220165045A1

公开(公告)日：2022-05-26

申请号：US17542497

申请日：2021-12-06

Applicant: HUAWEI TECHNOLOGIES CO.,LTD.

Inventor： Lihui Jiang ,  Zhan Qu ,  Wei Zhang

IPC: G06V10/22 ,  G06V10/25 ,  G06V10/77 ,  G06V10/75 ,  G06V10/82

Abstract: This application relates to the field of artificial intelligence, and specifically, to the field of computer vision, and discloses a perception network based on a plurality of headers. The perception network includes a backbone and the plurality of parallel headers. The plurality of parallel headers are connected to the backbone. The backbone is configured to receive an input image, perform convolution processing on the input image, and output feature maps, corresponding to the image, that have different resolutions. Each of the plurality of parallel headers is configured to detect a task object in a task based on the feature maps output by the backbone, and output a 2D box of a region in which the task object is located and confidence corresponding to each 2D box. Each parallel header detects a different task object.

公开(公告)号：US11478169B2

公开(公告)日：2022-10-25

申请号：US16846890

申请日：2020-04-13

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Yu Qiao ,  Wenbin Du ,  Yali Wang ,  Lihui Jiang ,  Jianzhuang Liu

IPC: A61B5/11 ,  A61B5/00 ,  G06N3/08 ,  G06V10/46 ,  G06V40/10

Abstract: Action recognition methods are disclosed. An embodiment of the methods includes: identifying a video that comprises images of a human body to be processed; identifying at least one image to be processed, wherein the at least one image is at least one of an optical flow image generated based on a plurality of frames of images in the video, or a composite image of one or more frames of images in the video; performing convolution on the at least one image to obtain a plurality of eigenvectors, wherein the plurality of eigenvectors indicate a plurality of features of different locations in the at least one image; determining a weight coefficient set of each of a plurality of human joints of the human body based on the plurality of eigenvectors, wherein the weight coefficient set comprises a weight coefficient of each of the plurality of eigenvectors for the human joint; weighting the plurality of eigenvectors based on the weight coefficient set to obtain an action feature of each of the plurality of human joints; determining an action feature of the human body based on the action feature of each of the human joints; and determining an action type of the human body based on the action feature of the human body.

公开(公告)号：US20210012164A1

公开(公告)日：2021-01-14

申请号：US17034654

申请日：2020-09-28

Applicant: Huawei Technologies Co., Ltd.

Inventor： Yu Qiao ,  Lei Zhou ,  Yali Wang ,  Lihui Jiang ,  Jianzhuang Liu

IPC: G06K9/62 ,  G06K9/00 ,  G06K9/46

Abstract: An action recognition method and apparatus related to artificial intelligence and include extracting a spatial feature of a to-be-processed picture, determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature and X spatial features and X optical flow features in a preset feature library, where the X spatial features and the X optical flow features include a one-to-one correspondence, determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature and Y optical flow features, where each of the Y optical flow features in the preset feature library corresponds to one action category, X and Y are both integers greater than 1, and determining an action category of the to-be-processed picture based on the first type of confidence.

公开(公告)号：US11704938B2

公开(公告)日：2023-07-18

申请号：US17846533

申请日：2022-06-22

Applicant: Huawei Technologies Co., Ltd.

Inventor： Yu Qiao ,  Lei Zhou ,  Yali Wang ,  Lihui Jiang ,  Jianzhuang Liu

IPC: G06K9/62 ,  G06V40/20 ,  G06V10/40 ,  G06V20/40 ,  G06V10/62 ,  G06V10/72 ,  G06V10/77 ,  G06V10/74 ,  G06F18/24 ,  G06F18/21 ,  G06F18/22 ,  G06F18/213 ,  G06V10/82

CPC classification number: G06V40/20 ,  G06F18/21 ,  G06F18/213 ,  G06F18/22 ,  G06F18/24 ,  G06V10/40 ,  G06V10/62 ,  G06V10/72 ,  G06V10/761 ,  G06V10/7715 ,  G06V10/82 ,  G06V20/41 ,  G06V20/46

Abstract: An action recognition method and apparatus related to artificial intelligence and include extracting a spatial feature of a to-be-processed picture, determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature and X spatial features and X optical flow features in a preset feature library, where the X spatial features and the X optical flow features include a one-to-one correspondence, determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature and Y optical flow features, where each of the Y optical flow features in the preset feature library corresponds to one action category, X and Y are both integers greater than 1, and determining an action category of the to-be-processed picture based on the first type of confidence.

公开(公告)号：US20220391645A1

公开(公告)日：2022-12-08

申请号：US17846533

申请日：2022-06-22

Applicant: Huawei Technologies Co., Ltd.

Inventor： Yu Qiao ,  Lei Zhou ,  Yali Wang ,  Lihui Jiang ,  Jianzhuang Liu

IPC: G06K9/62 ,  G06V10/40 ,  G06V20/40 ,  G06V10/62 ,  G06V10/72 ,  G06V10/77 ,  G06V10/74

Abstract: An action recognition method and apparatus related to artificial intelligence and include extracting a spatial feature of a to-be-processed picture, determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature and X spatial features and X optical flow features in a preset feature library, where the X spatial features and the X optical flow features include a one-to-one correspondence, determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature and Y optical flow features, where each of the Y optical flow features in the preset feature library corresponds to one action category, X and Y are both integers greater than 1, and determining an action category of the to-be-processed picture based on the first type of confidence.

公开(公告)号：US12169783B2

公开(公告)日：2024-12-17

申请号：US17586136

申请日：2022-01-27

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Qixiang Ye ,  Tianliang Zhang ,  Jianzhuang Liu ,  Xiaopeng Zhang ,  Qi Tian ,  Lihui Jiang

IPC: G06N3/084 ,  G06F18/25 ,  G06N3/045 ,  G06V10/20 ,  G06V10/77 ,  G06V10/80 ,  G06V10/82 ,  G06V20/40 ,  G06V20/52 ,  G06V20/58 ,  G06V40/10

Abstract: This application relates to the field of artificial intelligence and the field of computer vision. The method includes performing feature extraction on an image to obtain a basic feature map of the image, and determining a proposal of a region possibly including a pedestrian in the image. The basic feature map of the image is then processed to obtain an object visibility map in which a response to a pedestrian visible part is greater than a response to a pedestrian blocked part and a background part. The method further performs weighted summation processing on the object visibility map and the basic feature map to obtain an enhanced feature map of the image, and determines, based on the proposal of the image and the enhanced feature map of the image, a bounding box including a pedestrian in the image and a confidence level of the bounding box including the pedestrian.