Text-based Aerial-Ground Person Retrieval

• URL: http://arxiv.org/abs/2511.08369v1
• Date: Wed, 12 Nov 2025 01:55:55 GMT
• Title: Text-based Aerial-Ground Person Retrieval
• Authors: Xinyu Zhou, Yu Wu, Jiayao Ma, Wenhao Wang, Min Cao, Mang Ye,
• Abstract summary: This work introduces Text-based Aerial-Ground Person Retrieval (TAG-PR)<n>It aims to retrieve person images from heterogeneous aerial and ground views with textual descriptions.
• Score: 55.31140361809554
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This work introduces Text-based Aerial-Ground Person Retrieval (TAG-PR), which aims to retrieve person images from heterogeneous aerial and ground views with textual descriptions. Unlike traditional Text-based Person Retrieval (T-PR), which focuses solely on ground-view images, TAG-PR introduces greater practical significance and presents unique challenges due to the large viewpoint discrepancy across images. To support this task, we contribute: (1) TAG-PEDES dataset, constructed from public benchmarks with automatically generated textual descriptions, enhanced by a diversified text generation paradigm to ensure robustness under view heterogeneity; and (2) TAG-CLIP, a novel retrieval framework that addresses view heterogeneity through a hierarchically-routed mixture of experts module to learn view-specific and view-agnostic features and a viewpoint decoupling strategy to decouple view-specific features for better cross-modal alignment. We evaluate the effectiveness of TAG-CLIP on both the proposed TAG-PEDES dataset and existing T-PR benchmarks. The dataset and code are available at https://github.com/Flame-Chasers/TAG-PR.

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