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cs.CV2026

Parameter-Dynamic Adaptive Fusion and Calibration Network for RGBT Tracking

Zhaoding Ding, Chenglong Li, Jiandong Jin +2

Existing RGBT trackers typically employ fusion functions with fixed parameters across different targets and scenarios. Although dynamic-architecture methods improve fusion flexibil…

cs.CV2026

DRGBT-1K: A Large-scale High-quality Benchmark for Dynamic RGBT Tracking

Zhaodong Ding, Chenglong Li, Zeyu Ding +2

Dynamic RGBT (DRGBT) tracking aims to continuously localize a target when the available sensing modalities and observation platforms vary over time. Compared with conventional RGBT…

cs.CV2026

Cross-Modal UAV Object Tracking: State-Aware Representation Learning and A Unified Benchmark

Yun Xiao, Zhihong Hong, Jiandong Jin +3

Unmanned Aerial Vehicle (UAV) object tracking has emerged as a popular research field with broad practical applications. Modern UAVs are increasingly equipped with both visible lig…

cs.CV2026

RefAerial: A Benchmark and Approach for Referring Detection in Aerial Images

Guyue Hu, Hao Song, Yuxing Tong +5

Referring detection refers to locate the target referred by natural languages, which has recently attracted growing research interests. However, existing datasets are limited to gr…

cs.CV2026

Cross-modal Fuzzy Alignment Network for Text-Aerial Person Retrieval and A Large-scale Benchmark

Yifei Deng, Chenglong Li, Yuyang Zhang +2

Text-aerial person retrieval aims to identify targets in UAV-captured images from eyewitness descriptions, supporting intelligent transportation and public security applications. C…

cs.CV2026

Sparse-Dense Mixture of Experts Adapter for Multi-Modal Tracking

Yabin Zhu, Jianqi Li, Chenglong Li +3

Parameter-efficient fine-tuning (PEFT) techniques, such as prompts and adapters, are widely used in multi-modal tracking because they alleviate issues of full-model fine-tuning, in…