May 2, 2024, 4:44 a.m. | Zhangyong Tang, Tianyang Xu, Zhenhua Feng, Xuefeng Zhu, He Wang, Pengcheng Shao, Chunyang Cheng, Xiao-Jun Wu, Muhammad Awais, Sara Atito, Josef Kittle

cs.CV updates on arXiv.org arxiv.org

arXiv:2405.00168v1 Announce Type: new
Abstract: RGBT tracking draws increasing attention due to its robustness in multi-modality warranting (MMW) scenarios, such as nighttime and bad weather, where relying on a single sensing modality fails to ensure stable tracking results. However, the existing benchmarks predominantly consist of videos collected in common scenarios where both RGB and thermal infrared (TIR) information are of sufficient quality. This makes the data unrepresentative of severe imaging conditions, leading to tracking failures in MMW scenarios. To bridge …

arxiv benchmark benchmarks cs.cv perspective tracking type

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