Laser & Optoelectronics Progress, Volume. 62, Issue 14, 1412004(2025)

Indoor Monocular Depth Estimation Based on Global-Local Feature Fusion

Zengyu Tian, Changku Sun, Yue Li, Luhua Fu, and Peng Wang*
Author Affiliations
  • State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300372, China
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    Figures & Tables(13)
    Overall model structure
    DepthHead module
    Single-layer Transformer encoder architecture
    Simple pyramid pooling module
    Gated adaptive aggregation module
    DySample module
    Multi-kernel convolution module
    The relationship between Params and RMSE for each method
    Comparison of depth maps predicted by each method in different indoor scenes. (a) LapDepth; (b) GLPDepth; (c) proposed method; (d) ground truth
    Comparison of 3D reconstruction results for each method in different indoor scenes. (a) LapDepth; (b) GLPDepth; (c) proposed method; (d) ground truth
    Ablation visualization results of the MKCM
    • Table 1. Quantitative comparison of different methods on the NYU Depth V2 dataset

      View table

      Table 1. Quantitative comparison of different methods on the NYU Depth V2 dataset

      MethodParams /106Abs RelRMSElog RMSElog MAEδ<1.25δ<1.252δ<1.253
      Method of reference [351410.1580.6410.2140.7690.9500.988
      BTS21470.1100.3920.1420.0470.8850.9780.994
      AdaBins36780.1030.3640.0440.9030.9840.997
      LapDepth25730.1080.3850.1370.0460.8900.9820.996
      GLPDepth27620.1060.3750.1330.0450.8950.9840.996
      Method of reference [370.1070.3890.0420.8920.9870.998
      Proposed method610.1000.3610.1270.0430.9070.9860.997
    • Table 2. The ablation experimental results of the proposed method on the NYU Depth V2 dataset

      View table

      Table 2. The ablation experimental results of the proposed method on the NYU Depth V2 dataset

      ABCRuning time /msAbs RelRMSElog RMSElog MAEδ<1.25δ<1.252δ<1.253
      ×××18.20.1050.3760.1330.0450.8970.9840.996
      ××18.50.1020.3690.1300.0440.9030.9860.997
      ××22.70.1030.3620.1290.0440.9010.9850.997
      ××18.70.1020.3700.1310.0450.9050.9850.997
      ×22.90.1000.3590.1270.0430.9060.9870.997
      ×18.70.1010.3650.1290.0440.9080.9870.997
      ×22.90.1020.3660.1290.0440.9030.9860.997
      23.10.1000.3610.1270.0430.9070.9860.997
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    Zengyu Tian, Changku Sun, Yue Li, Luhua Fu, Peng Wang. Indoor Monocular Depth Estimation Based on Global-Local Feature Fusion[J]. Laser & Optoelectronics Progress, 2025, 62(14): 1412004

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Jan. 2, 2025

    Accepted: Feb. 25, 2025

    Published Online: Jul. 16, 2025

    The Author Email: Peng Wang (wang_peng@tju.edu.cn)

    DOI:10.3788/LOP250436

    CSTR:32186.14.LOP250436

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