Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0410012(2021)

Text Image Generation Method with Scene Description

Youwen Huang, Bin Zhou*, and Xin Tang
Author Affiliations
  • School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China
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    Figures & Tables(10)
    Generation network model
    Mask generation network
    Discrimination network model
    Layout discriminator
    Comparison results of same description
    Comparison results after adding objects
    Comparison results of predicted mask
    • Table 1. Preprocessing results under different threshold values

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      Table 1. Preprocessing results under different threshold values

      t0.30.40.50.60.7
      Number of objects156151146127103
      Number of relationship types3838373024
    • Table 2. Comparison results of IS and FID values

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      Table 2. Comparison results of IS and FID values

      ModelISFID
      Real image(64×64)13.90±0.500
      Proposed model(no Dlayout)6.72±0.2457.48
      Proposed model(no Gmask)6.69±0.1461.34
      Proposed model(full model)7.11±0.1442.20
      Sg2im[11]6.30±0.2073.39
      StackGAN[8]6.35±0.16108.68
      AttnGAN[10]6.38±0.2296.40
    • Table 3. Comparison results of image generation time

      View table

      Table 3. Comparison results of image generation time

      ModelProposed model(full model)Sg2im[11]StackGAN[8]AttnGAN[10]
      Time/s0.02780.02160.06340. 0302
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    Youwen Huang, Bin Zhou, Xin Tang. Text Image Generation Method with Scene Description[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410012

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    Paper Information

    Category: Image Processing

    Received: Jun. 30, 2020

    Accepted: Aug. 7, 2020

    Published Online: Feb. 24, 2021

    The Author Email: Zhou Bin (zhoubin_master@163.com)

    DOI:10.3788/LOP202158.0410012

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