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Dynamic Aggregated Network for Gait Recognition

CVPR 2023 · Video › Video segmentation and tracking · approach: Spatio-temporal predictive modeling · 79 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use DANet instead of LagrangeGaitgait recognition · CASIA-B CLrank-1 accuracy (%): 85.1 -> 89.9Helped
Add LCMB instead of using C2D convolution (ablation)DANet · CASIA-B CLrank-1 accuracy (%): 84.3 -> 89.9Helped
Add LCMB instead of using C3D convolution (ablation)DANet · CASIA-B CLrank-1 accuracy (%): 87.7 -> 89.9Helped
Add GMPA instead of Max aggregation (ablation)DANet with LCMB · CASIA-B CLrank-1 accuracy (%): 86.9 -> 89.9Helped
Add GMPA instead of Mean aggregation (ablation)DANet with LCMB · CASIA-B CLrank-1 accuracy (%): 87.1 -> 89.9Helped
Add GMPA instead of GeM aggregation (ablation)DANet with LCMB · CASIA-B CLrank-1 accuracy (%): 85.3 -> 89.9Helped
Add GMPA instead of MCM aggregation (ablation)DANet with LCMB · CASIA-B CLrank-1 accuracy (%): 85.4 -> 89.9Helped
Set spatial parts Npart=16 rather than 64 (ablation)DANet · CASIA-B meanrank-1 accuracy (%): 94.6 -> 92.5Hurt
Set spatial parts Npart=32 rather than 64 (ablation)DANet · CASIA-B meanrank-1 accuracy (%): 94.6 -> 94.2Hurt
Set lower-order motion patterns Npatt=1 rather than 16 (ablation)DANet · CASIA-B meanrank-1 accuracy (%): 94.6 -> 93.4Hurt
Set lower-order motion patterns Npatt=8 rather than 16 (ablation)DANet · CASIA-B meanrank-1 accuracy (%): 94.6 -> 93.1Hurt
Set lower-order motion patterns Npatt=32 rather than 16 (ablation)DANet · CASIA-B meanrank-1 accuracy (%): 94.6 -> 93.6Hurt

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