SiamMN: Siamese modulation network for visual object tracking
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-020-09546-6.pdf
Reference39 articles.
1. L Bertinetto, J Valmadre, JF Henriques, et al. (2016). Fully-convolutional Siamese networks for object tracking[C]. 2016 European Conference on Computer Vision(ECCV), Springer International publishing
2. G Bhat, J Johnander, M Danelljan, et al. (2018). Unveiling the Power of Deep Tracking[C]. 2018 European Conference on Computer Vision(ECCV), Springer International publishing
3. DS Bolme, JR Beveridge, BA Draper, et al (2010). Visual object tracking using adaptive correlation filters[C], 2010 IEEE conference on computer vision and pattern recognition(CVPR), IEEE
4. F Chelsea, A Pieter, L Sergey (2017). Model-agnostic meta-learning for fast adaptation of deep networks. arXiv preprint arXiv: 1703.03400
5. M Danelljan, G Bhat, F Shahbaz Khan, and M Felsberg (2017) [C]. Eco: Efficient convolution operators for tracking. 2017 IEEE conference on computer vision and pattern recognition(CVPR), IEEE
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