High Speed and Robust RGB-Thermal Tracking via Dual Attentive Stream Siamese Network

Author:

Guo Chaoyang1,Xiao Liang1

Affiliation:

1. School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Reference10 articles.

1. Fusing two-stream convolutional neural networks for RGB-T object tracking

2. Weighted Sparse Representation Regularized Graph Learning for RGB-T Object Tracking

3. LasHeR: A Large-Scale High-Diversity Benchmark for RGBT Tracking

4. Dual Siamese network for RGBT tracking via fusing predicted position maps;guo;The Visual Computer,2021

5. SiamFT: An RGB-infrared fusion tracking method via fully convolutional siamese networks;zhang;IEEE Access,0

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. TEFNet: Target-Aware Enhanced Fusion Network for RGB-T Tracking;Pattern Recognition and Computer Vision;2023-12-25

2. Mask Refined Deep Fusion Network With Dynamic Memory for Robust RGBT Tracking;2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI);2023-08-18

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