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Fully-Convolutional Siamese Networks for Object Tracking
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“Current prevailing trackers, including both the offline Siamese trackers and the online learning models, are almost all build upon convolutional operations [2, 37, 3, 47].”
From Learning Spatio-Temporal Transformer for Visual Tracking (2021) · cites this paper as [2]
In the citing paper
“For most of the popular trackers (such as SiamFC [1], SiamRPN [22], and ATOM [9]), correlation plays a critical role in integrating the template or target information into the regions of interest (ROI).”
From Transformer Tracking (2021) · cites this paper as [1]
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ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Ioffe, S., & Szegedy, C. (2015) · arXiv · doi:10.48550/arxiv.1502.03167 · Cited by 27,818
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
He, K., Zhang, X., Ren, S., & Sun, J. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.123 · Cited by 19,741
FaceNet: A unified embedding for face recognition and clustering
Schroff, F., Kalenichenko, D., & Philbin, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298682 · Cited by 15,267
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.220 · Cited by 6,542
High-Speed Tracking with Kernelized Correlation Filters
Henriques, J. F., Caseiro, R., Martins, P., & Batista, J. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2345390 · Cited by 5,753
Self-citationParkhi, O. M., Vedaldi, A., & Zisserman, A. (2015) · Procedings of the British Machine Vision Conference 2015 · doi:10.5244/c.29.41 · Cited by 5,479
Self-citationCNN Features Off-the-Shelf: An Astounding Baseline for Recognition
Razavian, A. S., Azizpour, H., Sullivan, J., & Carlsson, S. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2014.131 · Cited by 4,451
Flownet: Learning optical flow with convolutional networks
Dosovitskiy, A., Fischer, P., Ilg, E., Hausser, P., Hazirbas, C., Golkov, V., Smagt, P. V. D., Cremers, D., & Brox, T. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.316 · Cited by 4,313
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Li, B., Wu, W., Wang, Q., Zhang, F., Xing, J., & Yan, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00441 · Cited by 2,607
Deep Learning for 3D Point Clouds: A Survey
Guo, Y., Wang, H., Hu, Q., Liu, H., Liu, L., & Bennamoun, M. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3005434 · Cited by 2,575
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Daudt, R. C., Saux, B. L., & Boulch, A. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451652 · Cited by 1,872
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“, MDNet [42], TRACA [5], CFNet [50], SiamFC [4], StructSiam [59], DSiam [16], SINT [49] and VITAL [48]), correlation filter trackers with hand-crafted features (e.”
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Müller, M., Bibi, A., Giancola, S., Alsubaihi, S., & Ghanem, B. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01246-5_19 · Cited by 1,192
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Zhang, Z., & Peng, H. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00472 · Cited by 1,160
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Liu, S., Liu, L., Tang, J., Yu, B., Wang, Y., & Shi, W. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2915983 · Cited by 778
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He, A., Luo, C., Tian, X., & Zeng, W. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00508 · Cited by 713
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Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R. P., Čehovin, L., Vojíř, T., Hager, G., Lukežič, A., Fernández, G., et al. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-48881-3_54 · Cited by 689
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Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R. P., Zajc, L. Č., Vojíř, T., Bhat, G., Lukežič, A., Eldesokey, A., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-11009-3_1 · Cited by 669
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Wang, Q., Teng, Z., Xing, J., Gao, J., Hu, W., & Maybank, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00510 · Cited by 604
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Gao, J., Zhang, T., & Xu, C. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00478 · Cited by 343
HiFT: Hierarchical Feature Transformer for Aerial Tracking
Cao, Z., Fu, C., Ye, J., Li, B., & Li, Y. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01517 · Cited by 354
Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking
Fan, H., & Ling, H. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.585 · Cited by 330
Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking
Chen, B., Li, P., Bai, L., Qiao, L., Shen, Q., Li, B., Gan, W., Wu, W., & Ouyang, W. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20047-2_22 · Cited by 345
Vision-Based Anti-UAV Detection and Tracking
Zhao, J. W., Zhang, J., Li, D., & Wang, D. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3177627 · Cited by 330
End-to-End Flow Correlation Tracking with Spatial-Temporal Attention
Zhu, Z. D., Wu, W., Zou, W., & Yan, J. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00064 · Cited by 322
High-Performance Long-Term Tracking With Meta-Updater
Dai, K., Zhang, Y., Wang, D., Li, J., Lu, H., & Yang, X. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00633 · Cited by 310
Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline
Zhang, P., Zhao, J. W., Wang, D., Lu, H., & Ruan, X. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00868 · Cited by 308
DCFNet: Discriminant Correlation Filters Network for Visual TrackingPreprint
Wang, Q., Gao, J. G., Xing, J., Zhang, M., & Hu, W. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.04057 · Cited by 305
Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark
Wang, X., Shu, X., Zhang, Z., Jiang, B., Wang, Y., Tian, Y., & Wu, F. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01355 · Cited by 315
D3S – A Discriminative Single Shot Segmentation Tracker
Lukezic, A., Matas, J., & Kristan, M. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00716 · Cited by 300
Jung, I., Son, J., Baek, M., & Han, B. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01225-0_6 · Cited by 297
TCTrack: Temporal Contexts for Aerial Tracking
Cao, Z., Huang, Z., Pan, L., Zhang, S., Liu, Z., & Fu, C. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01438 · Cited by 310
Self-Supervised Deep Correlation Tracking
Yuan, D., Chang, X., Huang, P.-Y., Liu, Q., & He, Z. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3037518 · Cited by 288
Fast and Accurate Online Video Object Segmentation via Tracking Parts
Cheng, J., Tsai, Y., Hung, W.-C., Wang, S., & Yang, M. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00774 · Cited by 284
GlobalTrack: A Simple and Strong Baseline for Long-Term Tracking
Huang, L., Zhao, X., & Huang, K. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6758 · Cited by 279
Metadata
- Authors
- Bertinetto, L., Valmadre, J., Henriques, J. F., Vedaldi, A., & Torr, P. H. S.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Bertinetto, Luca
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 850-865
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2470394683
- Cited by
- 4,546
- References
- 49
- Citations by year
- 2026: 201 · 2025: 434 · 2024: 567 · 2023: 591 · 2022: 663 · 2021: 641 · 2020: 563 · 2019: 507 · 2018: 273 · 2017: 102 · 2016: 3
- FWCI
- 100.19
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Oxford University Research Archive (ORA) (University of Oxford) (acceptedVersion)
- Funders
- Engineering and Physical Sciences Research Council (EP/L024683/1, EP/N019474/1)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- object tracking, Siamese network, fully convolutional network, end-to-end learning, online learning, appearance modeling, video object detection, real-time tracking
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