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Head and Body: Unified Detector and Graph Network for Person Search in Media

arXiv 2111.13888 ↗First posted 27 Nov 2021cs.CVcited by 1

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Abstract (arXiv)

Person search in media has seen increasing potential in Internet applications, such as video clipping and character collection. This task is common but overlooked by previous person search works which focus on surveillance scenes. The media scenarios have some different challenges from surveillance scenes. For example, a person may change his clothes frequently. To alleviate this issue, this paper proposes a Unified Detector and Graph Network (UDGNet) for person search in media. UDGNet is the first person search framework to detect and re-identify the human body and head simultaneously. Specifically, it first builds two branches based on a unified network to detect the human body and head, then the detected body and head are used for re-identification. This dual-task approach can significantly enhance discriminative learning. To tackle the cloth-changing issue, UDGNet builds two graphs to explore reliable links among cloth-changing samples and utilizes a graph network to learn better embeddings. This design effectively enhances the robustness of person search to cloth-changing challenges. Besides, we demonstrate that UDGNet can be implemented with both anchor-based and anchor-free person search frameworks and further achieve performance improvement. This paper also contributes a large-scale dataset for Person Search in Media (PSM), which provides both body and head annotations. It is by far the largest dataset for person search in media. Experiments show that UDGNet improves the anchor-free model AlignPS by 12.1% in mAP. Meanwhile, it shows good generalization across surveillance and longterm scenarios. The dataset and code will be available at: https://github.com/shuxjweb/PSM.git.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 39 of its 52 references that are in the map. First posted on arXiv 27 Nov 2021.

Builds on

39 of 52 references.

References · 39

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27 more
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  1. 2023BPJDet: Extended Object Representation for Generic Body-Part Joint Detectioncited by 2