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cs.CV2025

X-ReID: Multi-granularity Information Interaction for Video-Based Visible-Infrared Person Re-Identification

Chenyang Yu, Xuehu Liu, Pingping Zhang +1

Large-scale vision-language models (e.g., CLIP) have recently achieved remarkable performance in retrieval tasks, yet their potential for Video-based Visible-Infrared Person Re-Ide…

cs.CV2025

Spatial-Frequency Enhanced Mamba for Multi-Modal Image Fusion

Hui Sun, Long Lv, Pingping Zhang +4

Multi-Modal Image Fusion (MMIF) aims to integrate complementary image information from different modalities to produce informative images. Previous deep learning-based MMIF methods…

cs.CV2025

LATex: Leveraging Attribute-based Text Knowledge for Aerial-Ground Person Re-Identification

Pingping Zhang, Xiang Hu, Yuhao Wang +1

As an important task in intelligent transportation systems, Aerial-Ground person Re-IDentification (AG-ReID) aims to retrieve specific persons across heterogeneous cameras in diffe…

cs.CV2025

What Makes You Unique? Attribute Prompt Composition for Object Re-Identification

Yingquan Wang, Pingping Zhang, Chong Sun +2

Object Re-IDentification (ReID) aims to recognize individuals across non-overlapping camera views. While recent advances have achieved remarkable progress, most existing models are…

cs.CV2025

AG-VPReID 2025: Aerial-Ground Video-based Person Re-identification Challenge Results

Kien Nguyen, Clinton Fookes, Sridha Sridharan +20

Person re-identification (ReID) across aerial and ground vantage points has become crucial for large-scale surveillance and public safety applications. Although significant progres…

cs.CV2025

IDEA: Inverted Text with Cooperative Deformable Aggregation for Multi-modal Object Re-Identification

Yuhao Wang, Yongfeng Lv, Pingping Zhang +1

Multi-modal object Re-IDentification (ReID) aims to retrieve specific objects by utilizing complementary information from various modalities. However, existing methods focus on fus…