The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Robust Visual Tracking via Structured Multi-Task Sparse Learning
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Citations
Cites
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Beck, A., & Teboulle, M. (2009) · SIAM Journal on Imaging Sciences · doi:10.1137/080716542 · Cited by 11,952
CONDENSATION—Conditional Density Propagation for Visual Tracking
Isard, M., & Blake, A. (1998) · International Journal of Computer Vision · doi:10.1023/a:1008078328650 · Cited by 4,886
Comaniciu, D., Ramesh, V., & Meer, P. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1195991 · Cited by 4,560
Incremental Learning for Robust Visual Tracking
Ross, D. A., Lim, J., Lin, R.-S., & Yang, M.-H. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-007-0075-7 · Cited by 3,061
Visual tracking and recognition using appearance-adaptive models in particle filters
Zhou, S. K., Chellappa, R., & Moghaddam, B. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2004.836152 · Cited by 668 · cited 1×
“In Zhou et al. (2004), the number of particle samples is adjusted according to an adaptive noise component.”
Method
Cited by
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
Wu, Y., Lim, J., & Yang, M.-H. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2388226 · Cited by 3,371
A Survey on Multi-Task Learning
Zhang, Y., & Yang, Q. (2017) · arXiv · doi:10.48550/arxiv.1707.08114 · Cited by 2,910
Encoding Color Information for Visual Tracking: Algorithms and Benchmark
Liang, P., Blasch, E., & Ling, H. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2482905 · Cited by 726
Multi-task Correlation Particle Filter for Robust Object Tracking
Zhang, T., Xu, C., & Yang, M.-H. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.512 · Cited by 426
Self-citation
Metadata
- Authors
- Zhang, T., Ghanem, B., Liu, S., & Ahuja, N.
- Venue
- International Journal of Computer Vision
- Published
- 2012-11-09
- Volume
- 101
- Issue
- 2
- Pages
- 367-383
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W2102674365
- Cited by
- 426
- References
- 5
- FWCI
- 54.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Robust Visual Tracking via Structured Multi-Task Sparse Learning. https://app.cochat.ai/papers/10.1007/s11263-012-0582-z
- The paper
- Zhang, T., Ghanem, B., Liu, S., & Ahuja, N. (2013). Robust Visual Tracking via Structured Multi-Task Sparse Learning. International Journal of Computer Vision. https://doi.org/10.1007/s11263-012-0582-z
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.
