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PSTR: End-to-End One-Step Person Search With Transformers

CVPR 2022 · Detection and segmentation › CNN features · approach: Pedestrian and crowd detection · 85 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use PSTR with ResNet50 instead of AlignPS with ResNet50Person search on PRW · PRW testmAP: 45.9 -> 49.5Helped
Use shared multi-level re-id decoding instead of single-level re-id decoding (ablation)PSTR · PRW testmAP: 47.4 -> 51.9Helped
Use shared multi-level re-id decoding instead of single-level re-id decoding (ablation)PSTR · PRW testTop-1: 84.9 -> 88.3Helped
Use shared re-id decoder instead of parallel re-id decoders (ablation)PSTR · PRW testmAP: 51.4 -> 51.9Helped
Use backbone P4 features rather than detection encoder features as re-id input (ablation)PSTR · PRW testmAP: 47.5 -> 51.9Helped
Use part attention instead of deformable attention (ablation)PSTR re-id decoder · PRW testmAP: 51.5 -> 51.9Helped
Use part attention instead of deformable attention (ablation)PSTR re-id decoder · PRW testTop-1: 87.8 -> 88.3Helped
Add P3 to the P4 re-id scale (ablation)PSTR multi-scale re-id decoder · PRW testmAP: 51.9 -> 54.7Helped
Add P2 to the P4+P3 re-id scales (ablation)PSTR multi-scale re-id decoder · PRW testmAP: 54.7 -> 56.5Helped
Use PSTR's person-search-specialized module instead of a shared standard encoder-decoder (ablation)One-step transformer person search · PRW testmAP: 23.1 -> 51.9Helped
Use PSTR's person-search-specialized module instead of separate detection and re-id encoder-decoders (ablation)One-step transformer person search · PRW testmAP: 44.5 -> 51.9Helped
Use the PVTv2-B2 backbone instead of ResNet50PSTR · PRW testmAP: 49.5 -> 56.5Helped

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