• Laser & Optoelectronics Progress
  • Vol. 59, Issue 24, 2420001 (2022)
Hao Chen1, Baohua Zhang1、3、*, Xiaoqi Lü2、3, Yu Gu1、3, Yueming Wang1、3, Xin Liu1、3, Yan Ren1, Jianjun Li1、3, and Ming Zhang1、3
Author Affiliations
  • 1School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, Inner Mongolia, China
  • 2School of Information Engineering, Mongolia Industrial University, Huhehaote010051, Inner Mongolia, China
  • 3Inner Mongolia Key Laboratory of Patten Recognition and Intelligent Image Processing, Baotou 014010, Inner Mongolia, China
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    DOI: 10.3788/LOP202259.2420001 Cite this Article Set citation alerts
    Hao Chen, Baohua Zhang, Xiaoqi Lü, Yu Gu, Yueming Wang, Xin Liu, Yan Ren, Jianjun Li, Ming Zhang. Soft Pseudo-Label and Multi-Scale Feature Fusion for Person Re-Identification[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2420001 Copy Citation Text show less
    Model of soft pseudo-label correction based on improved SPGAN
    Fig. 1. Model of soft pseudo-label correction based on improved SPGAN
    Generator structure diagram for SPGAN
    Fig. 2. Generator structure diagram for SPGAN
    Multiple scale feature reconstruction model
    Fig. 3. Multiple scale feature reconstruction model
    Visual examples of image-image translation
    Fig. 4. Visual examples of image-image translation
    Visual collation map of model characteristic pattern
    Fig. 5. Visual collation map of model characteristic pattern
    MethodMarket1501→Duke-MTMC-reIDDuke-MTMC-reID→Market1501
    mAPRank 1Rank 5Rank 10mAPRank 1Rank 5Rank 10
    ResNet-50-DBSCAN54.271.182.586.060.875.084.789.4
    Soft pseudo-label-ResNet-50-DBSCAN63.577.587.693.171.488.395.697.5
    Soft pseudo-label-IBN-a-ResNet-50-DBSCAN67.280.289.992.776.689.795.497.7
    Table 1. Results of soft pseudo-label correction method verification experiment
    MethodMarket1501→Duke-MTMC-reIDDuke-MTMC-reID→Market1501
    mAPRank 1Rank 5Rank 10mAPRank 1Rank 5Rank 10
    Soft pseudo-label-IBN-a-ResNet-50-DBSCAN67.280.289.992.776.689.795.497.7
    SPGAN-soft pseudo-label-IBN-a-ResNet-50-DBSCAN69.381.690.493.579.290.994.597.6
    Improved SPGAN-Soft pseudo-label-IBN-a-ResNet-50-DBSCAN70.285.892.195.780.492.597.298.4
    Table 2. Results of pseudo-label clustering algorithm based on the SPGAN model verification experiment
    MethodMarket1501→Duke-MTMC-reIDDuke-MTMC-reID→Market1501
    mAPRank 1Rank 5Rank 10mAPRank 1Rank 5Rank 10
    PAD-Net1745.163.277.082.547.675.286.390.2
    MMT-700/5002068.781.891.293.476.590.996.497.9
    AE2246.767.979.283.658.081.691.994.6
    Co-teaching-5001861.777.688.090.771.787.895.096.5
    ECN2140.463.375.880.443.075.187.691.6
    AD-Cluster1954.172.682.585.568.386.794.496.5
    PCB-PAST2354.372.4--54.678.4--
    SSG1653.473.080.683.258.380.090.092.4
    Proposed method70.285.892.195.780.492.597.298.4
    Table 3. Comparison of unsupervised person recognition accuracy with related methods
    Hao Chen, Baohua Zhang, Xiaoqi Lü, Yu Gu, Yueming Wang, Xin Liu, Yan Ren, Jianjun Li, Ming Zhang. Soft Pseudo-Label and Multi-Scale Feature Fusion for Person Re-Identification[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2420001
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