• Patent Title: Method of semantically segmenting input image, apparatus for semantically segmenting input image, method of pre-training apparatus for semantically segmenting input image, training apparatus for pre-training apparatus for semantically segmenting input image, and computer-program product
  • Application No.: US16960071
    Application Date: 2019-10-10
  • Publication No.: US11244196B2
    Publication Date: 2022-02-08
  • Inventor: Tingting Wang
  • Applicant: BOE Technology Group Co., Ltd.
  • Applicant Address: CN Beijing
  • Assignee: BOE Technology Group Co., Ltd.
  • Current Assignee: BOE Technology Group Co., Ltd.
  • Current Assignee Address: CN Beijing
  • Agency: Intellectual Valley Law, P.C.
  • Priority: CN201910489560.0 20190605
  • International Application: PCT/CN2019/110452 WO 20191010
  • International Announcement: WO2020/244108 WO 20201210
  • Main IPC: G06K9/46
  • IPC: G06K9/46 G06T7/10 G06K9/62
Method of semantically segmenting input image, apparatus for semantically segmenting input image, method of pre-training apparatus for semantically segmenting input image, training apparatus for pre-training apparatus for semantically segmenting input image, and computer-program product
Abstract:
A method of semantically segmenting an input image using a neural network is provided. The method includes extracting features of the input image to generate one or more feature maps; and analyzing the one or more feature maps to generate a plurality of predictions respectively corresponding to a plurality of subpixels of the input image. Extracting features of the input image is performed using a residual network having N number of residual blocks, N being a positive integer greater than 1. Analyzing the one or more feature maps is performed through M number of feature analyzing branches to generate M sets of predictions. A respective one set of the M sets of predictions includes multiple predictions respectively corresponding to the plurality of subpixels of the input image. A respective one of the plurality of predictions is an average value of corresponding ones of the M sets of predictions.
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