公开(公告)号：US11887354B2

公开(公告)日：2024-01-30

申请号：US17442697

申请日：2020-07-02

Applicant: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES

Inventor： Zhaoxiang Zhang ,  Tieniu Tan ,  Chunfeng Song ,  Junsong Fan

IPC: G06V10/40 ,  G06V10/764 ,  G06T7/174 ,  G06V10/774 ,  G06V20/70 ,  G06V10/776

CPC classification number: G06V10/765 ,  G06T7/174 ,  G06V10/40 ,  G06V10/776 ,  G06V10/7747 ,  G06V20/70 ,  G06T2207/20021 ,  G06T2207/20081

Abstract: A weakly supervised image semantic segmentation method based on an intra-class discriminator includes: constructing two levels of intra-class discriminators for each image-level class to determine whether pixels belonging to the image class belong to a target foreground or a background, and using weakly supervised data for training; generating a pixel-level image class label based on the two levels of intra-class discriminators, and generating and outputting a semantic segmentation result; and further training an image semantic segmentation module or network by using the label to obtain a final semantic segmentation model for an unlabeled input image. By means of the new method, intra-class image information implied in a feature code is fully mined, foreground and background pixels are accurately distinguished, and performance of a weakly supervised semantic segmentation model is significantly improved under the condition of only relying on an image-level annotation.

公开(公告)号：US11954599B2

公开(公告)日：2024-04-09

申请号：US17347608

申请日：2021-06-15

Applicant: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES

Inventor： Zhaoxiang Zhang ,  Tieniu Tan ,  Chunfeng Song ,  Wenkai Dong

IPC: G06V40/10 ,  G06F18/21 ,  G06F18/214 ,  G06F18/2415 ,  G06N3/045 ,  G06N3/08 ,  G06N3/084 ,  G06V20/40

CPC classification number: G06N3/084 ,  G06F18/2148 ,  G06F18/2193 ,  G06F18/2415 ,  G06N3/045 ,  G06N3/08 ,  G06V20/40 ,  G06V40/103

Abstract: A bi-directional interaction network (BINet)-based person search method, system, and apparatus are provided. The method includes: obtaining, as an input image, a tth frame of image in an input video; and normalizing the input image, and obtaining a search result of a to-be-searched target person by using a pre-trained person search model, where the person search model is constructed based on a residual network, and a new classification layer is added to a classification and regression layer of the residual network to obtain an identity classification probability of the target person. The method improves the accuracy of the person search.