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Prototype-Guided Saliency Feature Learning for Person Search

CVPR 2021 · Label-efficient and robust learning › Recognition and long-tail · approach: Supervised person re-identification · 74 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add prototype-guided attention at 7×7 resolution (ablation)OIM baseline · PRWmAP: 35.5 -> 40.3Helped
add prototype-guided attention at 7×7 resolution (ablation)OIM baseline · PRWtop1: 77.2 -> 79.9Helped
use self-attention without prototype guidance at 7×7 resolution (ablation)OIM baseline · PRWmAP: 35.5 -> 36.2Helped
increase self-attention saliency resolution to 14×14 (ablation)OIM baseline · PRWmAP: 36.2 -> 36.8Helped
increase prototype-guided saliency resolution to 14×14 (ablation)PGA · PRWmAP: 40.3 -> 42.7Helped
add adaptive momentum update with τ=0.03 (ablation)OIM baseline · PRWmAP: 35.5 -> 38.7Helped
add adaptive momentum update with τ=0.05 (ablation)OIM baseline · PRWmAP: 35.5 -> 38.9Helped
add adaptive momentum update with τ=0.1 (ablation)OIM baseline · PRWmAP: 35.5 -> 38.6Helped
remove adaptive momentum update from PGA (ablation)PGA · PRWmAP: 42.5 -> 40.3Hurt
add adaptive momentum update to PGA with τ=0.03 (ablation)PGA · PRWmAP: 40.3 -> 42.4Helped
add adaptive momentum update to PGA with τ=0.05 (ablation)PGA · PRWmAP: 40.3 -> 42.5Helped
add adaptive momentum update to PGA with τ=0.1 (ablation)PGA · PRWmAP: 40.3 -> 42.2Helped

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