Table 2 AP Scores across model types using the HRNet backbone

From: Neonatal pose estimation in the unaltered clinical environment with fusion of RGB, depth and IR images

Model

W32-256

W32-384

W48-384

RGB

0.753 ± 0.102

0.762 ± 0.095

0.779 ± 0.093

Depth

0.778 ± 0.082

0.769 ± 0.090

0.765 ± 0.091

IR

0.739 ± 0.099

0.747 ± 0.095

0.758 ± 0.096

EIF-RGB-D

0.761 ± 0.086

0.765 ± 0.090

0.768 ± 0.093

EIF-RGB-IR

0.747 ± 0.092

0.765 ± 0.089

0.715 ± 0.121

EIF-D-IR

0.780 ± 0.087

0.760 ± 0.094

0.785 ± 0.083

EIF-RGB-D-IR

0.763 ± 0.088

0.753 ± 0.092

0.773 ± 0.083

IIF-1

0.785 ± 0.083

0.788 ± 0.083

0.793 ± 0.086

IIF-2

0.800 ± 0.076

0.784 ± 0.090

0.774 ± 0.094

IIF-3

0.792 ± 0.077

0.790 ± 0.080

0.776 ± 0.094

IIF-4

0.753 ± 0.099

0.761 ± 0.100

0.771 ± 0.097

LIF-1

0.769 ± 0.088

0.775 ± 0.091

0.798 ± 0.078

LIF-2

0.757 ± 0.101

0.775 ± 0.089

0.771 ± 0.095

LIF-3

0.775 ± 0.089

0.802 ± 0.077

0.811 ± 0.069

LIF-4

0.749 ± 0.099

0.765 ± 0.100

0.772 ± 0.089

  1. Scores in bold are the best scores for each backbone.
  2. E/I/LIF Early/Intermediate/Late Image Fusion.
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