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

Source: [LEAPS: End-to-End One-Step Person Search With Learnable Proposals](<https://www.sota2.com/research/paper/68fa6ed41e209131cea4279d>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:07:49.028Z

Authors: Zhiqiang Dong, Jiale Cao, Rao Muhammad Anwer, Jin Xie, Fahad Khan, Yanwei Pang

Published: 2023-03-21T13:59:32.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Person Search on PRW v1 (test)](<https://www.sota2.com/research/sota/person-search-on-prw-v1-test.md>): Person Search; PRW v1 (test); mAP: 59.5.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2303.11859>)

[PDF](<https://arxiv.org/pdf/2303.11859.pdf>)