mlsanityData to 7 Oct 2026

LEAPS: End-to-End One-Step Person Search With Learnable Proposals

arXiv 2303.11859 ↗First posted 21 Mar 2023cs.CVcited by 1

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Abstract (arXiv)

We propose an end-to-end one-step person search approach with learnable proposals, named LEAPS. Given a set of sparse and learnable proposals, LEAPS employs a dynamic person search head to directly perform person detection and corresponding re-id feature generation without non-maximum suppression post-processing. The dynamic person search head comprises a detection head and a novel flexible re-id head. Our flexible re-id head first employs a dynamic region-of-interest (RoI) operation to extract discriminative RoI features of the proposals. Then, it generates re-id features using a plain and a hierarchical interaction re-id module. To better guide discriminative re-id feature learning, we introduce a diverse re-id sample matching strategy, instead of bipartite matching in detection head. Comprehensive experiments reveal the benefit of the proposed LEAPS, achieving a favorable performance on two public person search benchmarks: CUHK-SYSU and PRW. When using the same ResNet50 backbone, our LEAPS obtains a mAP score of 55.0%, outperforming the best reported results in literature by 1.7%, while achieving around a two-fold speedup on the challenging PRW dataset. Our source code and models will be released.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 33 of its 40 references that are in the map. First posted on arXiv 21 Mar 2023.

Builds on

33 of 40 references.

References · 33

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21 more
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  6. 2021Anchor-Free Person Searchcited by 42
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  8. 2019Query-guided End-to-End Person Searchcited by 40
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  15. 2022PSTR: End-to-End One-Step Person Search With Transformerscited by 26
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  17. 2020Diverse Knowledge Distillation for End-to-End Person Searchcited by 16
  18. 2021Exploring Visual Context for Weakly Supervised Person Searchcited by 16
  19. 2021Weakly Supervised Person Search with Region Siamese Networkscited by 14
  20. 2022OIMNet++: Prototypical Normalization and Localization-aware Learning for Person Searchcited by 12
  21. 2022Domain Adaptive Person Searchcited by 7

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Citing papers per year: 2024: 1.

1 paper.

  1. 2024Swap Path Network for Robust Person Search Pre-trainingcited by 0