Optoelectronic Technology, Volume. 43, Issue 1, 17(2023)

High Resolution Face Image Reconstruction Based on Deep Feature Embedding

Zhihui MIAO1, Yongai ZHANG2, Zhixian LIN2, and Jianpu LIN1、*
Author Affiliations
  • 1School of Advanced Manufacturing, Fuzhou University, Quanzhou Fujian362200, CHN
  • 2School of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, CHN
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    Figures & Tables(13)
    Generator network structure of StyleGAN2
    Reconstructed images in different embedding spaces
    Reconstruction results for different initialized w+
    Framework for reconstruction algorithm and evaluation
    Partially reconstructed face images
    Visual comparison with existing methods
    Distribution of feature similarity when feature extractor for reconstruction and evaluation frameworks both are Inception
    Distribution of feature similarity when feature extractor for reconstruction and evaluation frameworks are Inception and Xception respectively
    Reconstruction results of this paper and other methods
    • Table 1. TAR when feature extractor for reconstruction and evaluation frameworks both are Inception

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      Table 1. TAR when feature extractor for reconstruction and evaluation frameworks both are Inception

      数据集FAR/(%)阈值正常TAR/(%)Ⅰ型评估TAR/(%)Ⅱ型评估TAR/(%)
      LFW00.531 679.7710064.00
      0.10.438 298.1210096.04
      10.400 099.4210099.17
      100.352 299.8610099.72
      ColorFeret00.528 099.4610098.92
      0.10.465 5100100100
      10.423 9100100100
      100.371 2100100100
    • Table 2. TAR when feature extractor for reconstruction and evaluation frameworks are Inception and Xception respectively

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      Table 2. TAR when feature extractor for reconstruction and evaluation frameworks are Inception and Xception respectively

      数据集FAR/(%)阈值正常TAR/(%)Ⅰ型评估TAR/(%)Ⅱ型评估TAR/(%)
      LFW00.493 391.904023.11
      0.10.446 397.767448.71
      10.401 899.419276.24
      100.352 299.9010096.96
      ColorFeret00.507 899.645443.55
      0.10.481 999.827058.06
      10.430 01009086.56
      100.373 810010099.46
    • Table 3. TAR of different methods on LFW dataset at 0.1% FAR

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      Table 3. TAR of different methods on LFW dataset at 0.1% FAR

      方法特征提取器分辨率Ⅰ型评估TAR/(%)Ⅱ型评估TAR/(%)
      本文ArcFace1 024×1 024100.0096.04
      MappingArcFace1 024×1 0241.420.46
      NbNetFaceNet160×16095.2053.91
    • Table 4. The pass rate of reconstructed images on living detect APIs

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      Table 4. The pass rate of reconstructed images on living detect APIs

      活体检测API重建图像方法通过图像数未通过图像数通过率/(%)
      API 1NbNet01500
      Mapping1292186
      本文1331788.67
      API 2NbNet708046.67
      Mapping1104073.33
      本文1123874.67
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    Zhihui MIAO, Yongai ZHANG, Zhixian LIN, Jianpu LIN. High Resolution Face Image Reconstruction Based on Deep Feature Embedding[J]. Optoelectronic Technology, 2023, 43(1): 17

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    Paper Information

    Category: Research and Trial-manufacture

    Received: Sep. 26, 2022

    Accepted: --

    Published Online: Apr. 14, 2023

    The Author Email: LIN Jianpu (ljp@fzu.edu.cn)

    DOI:10.19453/j.cnki.1005-488x.2023.01.004

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