The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
MEEM: Robust Tracking via Multiple Experts Using Entropy Minimization
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Citations
Cites
Lecture Notes in Computer Science 1205
(1999) · Industrial Robot: An International Journal · doi:10.1108/ir.1999.04926fae.001 · Cited by 38,662
Yilmaz, A., Javed, O., & Shah, M. (2006) · ACM Computing Surveys · doi:10.1145/1177352.1177355 · Cited by 4,792
Online Object Tracking: A Benchmark
Wu, Y., Lim, J., & Yang, M.-H. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2013.312 · Cited by 4,138
Robust object tracking with online multiple instance learning
Babenko, B., Yang, M.-H., & Belongie, S. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.226 · Cited by 2,007
Struck: Structured output tracking with kernels
Hare, S., Saffari, A., & Torr, P. H. S. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126251 · Cited by 1,831
Non-parametric local transforms for computing visual correspondence
Zabih, R., & Woodfill, J. (1994) · Lecture Notes in Computer Science · doi:10.1007/bfb0028345 · Cited by 1,763
Semi-supervised Learning by Entropy Minimization
Grandvalet, Y., & Bengio, Y. (2004) · Cited by 1,582
Real-Time Tracking via On-line Boosting
Grabner, H., Grabner, M., & Bischof, H. (2006) · Procedings of the British Machine Vision Conference 2006 · doi:10.5244/c.20.6 · Cited by 1,198
Visual tracking via adaptive structural local sparse appearance model
Jia, X., Lu, H., & Yang, M.-H. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247880 · Cited by 1,188
Kwon, J., & Lee, K. M. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539821 · Cited by 1,164
Cited by
Learning Multi-domain Convolutional Neural Networks for Visual Tracking
Nam, H., & Han, B. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.465 · Cited by 2,806
ECO: Efficient Convolution Operators for Tracking
Danelljan, M., Bhat, G., Khan, F. S., & Felsberg, M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.733 · Cited by 2,805
A Benchmark and Simulator for UAV Tracking
Mueller, M., Smith, N., & Ghanem, B. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46448-0_27 · Cited by 1,944
Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking
Danelljan, M., Robinson, A., Shahbaz Khan, F., & Felsberg, M. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46454-1_29 · Cited by 1,853
GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild
Huang, L., Zhao, X., & Huang, K. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2957464 · Cited by 1,809
Metadata
- Authors
- Zhang, J., Ma, S., & Sclaroff, S.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2014
- Pages
- 188-203
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W182940129
- Cited by
- 1,117
- References
- 36
- FWCI
- 45.95
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: MEEM: Robust Tracking via Multiple Experts Using Entropy Minimization. https://app.cochat.ai/papers/10.1007/978-3-319-10599-4_13
- The paper
- Zhang, J., Ma, S., & Sclaroff, S. (2014). MEEM: Robust Tracking via Multiple Experts Using Entropy Minimization. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-10599-4_13
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
