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Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification

AAAI 2020 · Label-efficient and robust learning › Recognition and long-tail · approach: Supervised person re-identification · 100 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add viewpoint-aware adaptive label smoothing (ablation)VA-reID with adaptive identity label smoothing · Market-1501mAP: 86.97 -> 88.67Helped
add viewpoint-aware adaptive label smoothing (ablation)VA-reID with adaptive identity label smoothing · DukeMTMC-reIDmAP: 77.99 -> 78.86Helped
add center regularization (ablation)VA-reID with adaptive identity label smoothing · Market-1501mAP: 86.97 -> 88.25Helped
add center regularization (ablation)VA-reID with adaptive identity label smoothing · DukeMTMC-reIDmAP: 77.99 -> 78.25Helped
replace fixed label smoothing with adaptive identity label smoothing (ablation)identity classification · Market-1501mAP: 86.72 -> 86.97Helped
replace fixed label smoothing with adaptive identity label smoothing (ablation)identity classification · DukeMTMC-reIDmAP: 77.47 -> 77.99Helped
add local multi-stripe features (ablation)VA-reID · Market-1501mAP: 89.97 -> 91.70Helped
add local multi-stripe features (ablation)VA-reID · DukeMTMC-reIDmAP: 81.48 -> 84.51Helped
add reranking (ablation)VA-reID · Market-1501mAP: 91.70 -> 95.43Helped
use predicted viewpoints instead of ground-truth viewpoints (ablation)VA-reID · DukeMTMC-reIDmAP: 81.48 -> 81.05No clear effect
use pose-clustered viewpoints instead of ground-truth viewpoints (ablation)VA-reID · DukeMTMC-reIDmAP: 81.48 -> 80.69No clear effect

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