• Optics and Precision Engineering
  • Vol. 31, Issue 16, 2430 (2023)
Sen WANG, Yang ZHU, Yinhui ZHANG*, Qingjian WANG, and Zifen HE
Author Affiliations
  • Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China
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    DOI: 10.37188/OPE.20233116.2430 Cite this Article
    Sen WANG, Yang ZHU, Yinhui ZHANG, Qingjian WANG, Zifen HE. Multi-stage frame alignment video super- resolution network[J]. Optics and Precision Engineering, 2023, 31(16): 2430 Copy Citation Text show less
    Architecture of MSVSR
    Fig. 1. Architecture of MSVSR
    Deblurring stage
    Fig. 2. Deblurring stage
    Pre-aligned module
    Fig. 3. Pre-aligned module
    Sub-module in deblurring stage
    Fig. 4. Sub-module in deblurring stage
    Shift-MLP module
    Fig. 5. Shift-MLP module
    Feature fusion block
    Fig. 6. Feature fusion block
    Alignment stage[28]
    Fig. 7. Alignment stage28
    Reconstruction stage
    Fig. 8. Reconstruction stage
    Performance and model complexity comparison on Vid4 dataset for BD task
    Fig. 9. Performance and model complexity comparison on Vid4 dataset for BD task
    Qualitative comparison on REDS4[10]
    Fig. 10. Qualitative comparison on REDS410
    Qualitative comparison on Vid4[10]
    Fig. 11. Qualitative comparison on Vid410
    Qualitative comparison on Vimeo-90K-T[10]
    Fig. 12. Qualitative comparison on Vimeo-90K-T10
    Comparison of temporal profile
    Fig. 13. Comparison of temporal profile
    对比网络参数量/M运行时间/msBI(PSNR/SSIM)BD(PSNR/SSIM)
    REDS4Vid4Vid4Vimeo-90K-T
    Bicubic26.14/0.729 223.78/0.634 721.80/0.524 631.30/0.868 7
    VESPCN1325.35/0.755 7
    TOF1427.98/0.799 025.89/0.765 134.62/0.921 2
    DUF195.897428.63/0.825 127.38/0.832 936.87/0.944 7
    FRVSR335.113726.69/0.810 335.64/0.931 9
    SPMC15--25.88/0.775 2
    EDVR1220.637831.09/0.880 027.35/0.826 427.85/0.850 337.81/0.952 3
    EDVR-M123.311830.53/0.869 927.10/0.818 627.45/0.840 637.33/0.948 4
    MuCAN3930.88/0.875 0
    TGA405.830.88/0.875 0
    RLSP244.24927.48/0.838 836.49/0.940 3
    RSDN326.29427.92/0.850 537.23/0.947 1
    RRN413.44527.92/0.850 537.23/0.947 1
    PFNL433.029529.63/0.850 226.73/0.802 927.16/0.833 5-
    RBPN4212.21 50730.09/0.859 027.12/0.818 037.20/0.945 8
    BaiscVSR106.36331.42/0.890 927.24/0.825 127.96/0.855 337.53/0.949 8
    MSVSR3.524531.64/0.895 827.41/0.833 428.12/0.858 237.70/0.951 4
    Table 1. Quantitative comparison10
    FFBPre-alignedPSNRSSIM
    28.120.858 2
    ×28.110.858 8
    ×28.100.858 6
    ××28.080.856 9
    Table 2. Ablation tests on Vid4 dataset for BD task
    MethodParamsPSNRSSIM
    Shift-MLP(DWConv)3.53 M28.120.858 2
    Shift-MLP(Conv)3.91 M28.140.859 9
    Table 3. Quantitative comparison of different convolution decomposition approaches on Vid4 dataset for BD task
    Sen WANG, Yang ZHU, Yinhui ZHANG, Qingjian WANG, Zifen HE. Multi-stage frame alignment video super- resolution network[J]. Optics and Precision Engineering, 2023, 31(16): 2430
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