• Laser & Optoelectronics Progress
  • Vol. 59, Issue 8, 0815011 (2022)
Junwen Liu1, Yongjun Zhang1、*, Zhi Li1, Yong Zhao2, Xinyu Ran1, Zhongwei Cui3, and Mengjia Niu1
Author Affiliations
  • 1Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, College of Computer Science and Technology, Guizhou University, Guiyang , Guizhou 550025, China
  • 2School of Information Engineering, Peking University Shenzhen Graduate School, Shenzhen , Guangdong 518055, China
  • 3Big Data Science and Intelligent Engineering Research Institute, Guizhou Education University, Guiyang , Guizhou 550018, China
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    DOI: 10.3788/LOP202259.0815011 Cite this Article Set citation alerts
    Junwen Liu, Yongjun Zhang, Zhi Li, Yong Zhao, Xinyu Ran, Zhongwei Cui, Mengjia Niu. Head Detection Based on RDM-YOLOv3[J]. Laser & Optoelectronics Progress, 2022, 59(8): 0815011 Copy Citation Text show less
    YOLOv3 network structure diagram
    Fig. 1. YOLOv3 network structure diagram
    DenseNet network structure diagram
    Fig. 2. DenseNet network structure diagram
    DenseBlock internal structure diagram
    Fig. 3. DenseBlock internal structure diagram
    Structure of RD-Net feature extraction network
    Fig. 4. Structure of RD-Net feature extraction network
    MDC structure diagram
    Fig. 5. MDC structure diagram
    First MDC2 channel connection diagram
    Fig. 6. First MDC2 channel connection diagram
    Complete network structure diagram
    Fig. 7. Complete network structure diagram
    PR curves of ablation experiments on two datasets. (a) Brainwash dataset; (b) HollywoodHeads dataset
    Fig. 8. PR curves of ablation experiments on two datasets. (a) Brainwash dataset; (b) HollywoodHeads dataset
    Comparison of PR curves between RDM-YOLOv3 and other methods on Brainwash dataset
    Fig. 9. Comparison of PR curves between RDM-YOLOv3 and other methods on Brainwash dataset
    Comparison of PR curves between RDM-YOLOv3 and other methods on HollywoodHeads dataset
    Fig. 10. Comparison of PR curves between RDM-YOLOv3 and other methods on HollywoodHeads dataset
    Comparison of test results of two head datasets. (a) HollywoodHeads dataset; (b) Brainwash dataset
    Fig. 11. Comparison of test results of two head datasets. (a) HollywoodHeads dataset; (b) Brainwash dataset
    NetworkD-CBL of DenseBlock1D-CBL of DenseBlock2
    StructureConv (1×1×32)Conv (1×1×64)
    BNBN
    Leaky-ReLULeaky-ReLU
    Conv (3×3×64)Conv (3×3×128)
    BNBN
    Leaky-ReLULeaky-ReLU
    Table 1. Internal channel information of transport layer
    MethodAP (RIOU=0.5)FPS
    HollywoodHeadsBrainwash
    DarkNet-53 (baseline)0.6890.75219
    RD-Net0.7500.80128
    RD-Net+MDC10.7820.84625
    RD-Net+MDC1+MDC20.8230.88921
    RD-Net+MDC1+2×MDC20.8680.93116
    Table 2. Comparison of ablation experiments on two data sets
    MethodBackboneAP (RIOU=0.5)
    SSDVGG160.568
    FCHDVGG160.700
    YOLOv3DarkNet-530.768
    E2PDGoogLeNet+LSTM0.821
    FRCNVGG160.878
    HeadNetResNet-1010.910
    RDM-YOLOv3RD-Net+MDC0.931
    Table 3. Comparison results on Brainwash dataset
    MethodBackboneAP (RIOU=0.5)
    DPM-Face-0.370
    SSDVGG160.621
    YOLOv3DarkNet-530.689
    FRCNVGG160.712
    FCHDVGG160.743
    TKDLSTM0.750
    RDM-YOLOv3RD-Net+MDC0.868
    Table 4. Comparison results on HollywoodHeads dataset
    Junwen Liu, Yongjun Zhang, Zhi Li, Yong Zhao, Xinyu Ran, Zhongwei Cui, Mengjia Niu. Head Detection Based on RDM-YOLOv3[J]. Laser & Optoelectronics Progress, 2022, 59(8): 0815011
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