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Research map / 3D vision / Human pose estimation

Improving Person Re-Identification via Pose-Aware Multi-Shot Matching

CVPR 2016 · 3D vision › Human pose estimation · approach: Human shape and pose regression · 107 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add pose-aware multi-shot matching to KISSMEKISSME person re-identification · 3DPeS Set3Rank-1: 21.0 -> 68.4Helped
add pose-aware multi-shot matching to KISSMEKISSME person re-identification · 3DPeS Set4Rank-1: 25.0 -> 58.3Helped
add pose-aware multi-shot matching to KISSMEKISSME person re-identification · 3DPeS Set5Rank-1: 22.2 -> 55.6Helped
add pose-aware multi-shot matching to KISSMEKISSME person re-identification · 3DPeS Set AllRank-1: 26.5 -> 59.2Helped
add pose-aware multi-shot matching to KISSMEKISSME person re-identification · iLIDS-VidRank-1: 11.3 -> 30.3No clear effect
add pose-aware multi-shot matching to KISSMEKISSME person re-identification · PRID 2011Rank-1: 22.3 -> 45.0; 56.5Mixed
add sample selection based on sample confidence (ablation)PaMM · 3DPeS Set3AUC: 95.3 -> 96.4Helped
add sample selection based on sample confidence (ablation)PaMM · 3DPeS Set4AUC: 87.2 -> 88.9Helped
add sample selection based on sample confidence (ablation)PaMM · 3DPeS Set5AUC: 89.5 -> 88.6No clear effect
add sample selection based on sample confidence (ablation)PaMM · 3DPeS Set AllAUC: 92.7 -> 94.1Helped
train pose-pair matching weights instead of using uniform weights (ablation)PaMM · 3DPeS Set3AUC: 95.6 -> 96.4Helped
train pose-pair matching weights instead of using uniform weights (ablation)PaMM · 3DPeS Set4AUC: 88.9 -> 88.9No clear effect

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