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2011 · 11 papers

Efficiently learning a detection cascade with sparse eigenvectors

C. Shen, S. Paisitkriangkrai, J. Zhang

Citation:
C. Shen, S. Paisitkriangkrai, J. Zhang. Efficiently learning a detection cascade with sparse eigenvectors. IEEE Transactions on Image Processing. volume: 20, number: 1, pages: 22--35. 2011.

 @article{GSLDA2010Shen,
   author    = "C. Shen and  S. Paisitkriangkrai and  J. Zhang",
   title     = "Efficiently learning a detection cascade with sparse eigenvectors",
   journal   = "IEEE Transactions on Image Processing",
   volume    = "20",
   number    = "1",
   pages     = "22--35",
   url       = "http://dx.doi.org/10.1109/TIP.2010.2055880",
   year      = "2011",
 }

Incremental training of a detector using online sparse eigen-decomposition

S. Paisitkriangkrai, C. Shen, J. Zhang

Citation:
S. Paisitkriangkrai, C. Shen, J. Zhang. Incremental training of a detector using online sparse eigen-decomposition. IEEE Transactions on Image Processing. volume: 20, number: 1, pages: 213--226. 2011.

 @article{Incremental2010Shen,
   author    = "S. Paisitkriangkrai and  C. Shen and  J. Zhang",
   title     = "Incremental training of a detector using online sparse eigen-decomposition",
   journal   = "IEEE Transactions on Image Processing",
   volume    = "20",
   number    = "1",
   pages     = "213--226",
   url       = "http://dx.doi.org/10.1109/TIP.2010.2053548",
   year      = "2011",
 }

Efficiently learning a distance metric for large margin nearest neighbor classification

K. Park, C. Shen, Z. Hao, J. Kim

Citation:
K. Park, C. Shen, Z. Hao, J. Kim. Efficiently learning a distance metric for large margin nearest neighbor classification. National Conference on Artificial Intelligence (AAAI'11). pages: 453--458. 2011.

 @inproceedings{AAAI2011,
   author    = "K. Park and  C. Shen and  Z. Hao and  J. Kim",
   title     = "Efficiently learning a distance metric for large margin nearest neighbor classification",
   booktitle = "National Conference on Artificial Intelligence (AAAI'11)",
   pages     = "453--458",
   address   = "San Francisco, USA",
   year      = "2011",
 }

A direct formulation for totally-corrective multi-class boosting

C. Shen, Z. Hao

Citation:
C. Shen, Z. Hao. A direct formulation for totally-corrective multi-class boosting. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11). pages: 2585--2592. 2011.

 @inproceedings{Shen2011CVPRa,
   author    = "C. Shen and  Z. Hao",
   title     = "A direct formulation for totally-corrective multi-class boosting",
   booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11)",
   pages     = "2585--2592",
   address   = "Colorado Springs, USA",
   year      = "2011",
 }

A generalized probabilistic framework for compact codebook creation

L. Liu, L. Wang, C. Shen

Citation:
L. Liu, L. Wang, C. Shen. A generalized probabilistic framework for compact codebook creation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11). pages: 1537--1544. 2011.

 @inproceedings{Liu2011CVPR,
   author    = "L. Liu and  L. Wang and  C. Shen",
   title     = "A generalized probabilistic framework for compact codebook creation",
   booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11)",
   pages     = "1537--1544",
   address   = "Colorado Springs, USA",
   year      = "2011",
 }

Is face recognition really a compressive sensing problem?

Q. Shi, A. Eriksson, A. van den Hengel, C. Shen

Citation:
Q. Shi, A. Eriksson, A. van den Hengel, C. Shen. Is face recognition really a compressive sensing problem?. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11). pages: 553--560. 2011.

 @inproceedings{Shi2011CVPR,
   author    = "Q. Shi and  A. Eriksson and  A. van den Hengel and  C. Shen",
   title     = "Is face recognition really a compressive sensing problem?",
   booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11)",
   pages     = "553--560",
   address   = "Colorado Springs, USA",
   year      = "2011",
 }

Real-time visual tracking using compressive sensing

H. Li, C. Shen, Q. Shi

Citation:
H. Li, C. Shen, Q. Shi. Real-time visual tracking using compressive sensing. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11). pages: 1305--1312. 2011.

 @inproceedings{Li2011CVPR,
   author    = "H. Li and  C. Shen and  Q. Shi",
   title     = "Real-time visual tracking using compressive sensing",
   booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11)",
   pages     = "1305--1312",
   address   = "Colorado Springs, USA",
   year      = "2011",
 }

A scalable dual approach to semidefinite metric learning

C. Shen, J. Kim, L. Wang

Citation:
C. Shen, J. Kim, L. Wang. A scalable dual approach to semidefinite metric learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11). pages: 2601--2608. 2011.

 @inproceedings{Shen2011CVPRb,
   author    = "C. Shen and  J. Kim and  L. Wang",
   title     = "A scalable dual approach to semidefinite metric learning",
   booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11)",
   pages     = "2601--2608",
   address   = "Colorado Springs, USA",
   year      = "2011",
 }

On the optimality of sequential forward feature selection using class separability measure

L. Wang, C. Shen, R. Hartley

Citation:
L. Wang, C. Shen, R. Hartley. On the optimality of sequential forward feature selection using class separability measure. International Conference on Digital Image Computing: Techniques and Applications (DICTA'11). pages: 203--208. 2011.

 @inproceedings{DICTA2011b,
   author    = "L. Wang and  C. Shen and  R. Hartley",
   title     = "On the optimality of sequential forward feature selection using class separability measure",
   booktitle = "International Conference on Digital Image Computing: Techniques and Applications (DICTA'11)",
   pages     = "203--208",
   address   = "Queensland, Australia",
   year      = "2011",
 }

Laplacian margin distribution boosting for learning from sparsely labeled data

T. Wang, X. He, C. Shen, N. Barnes

Citation:
T. Wang, X. He, C. Shen, N. Barnes. Laplacian margin distribution boosting for learning from sparsely labeled data. International Conference on Digital Image Computing: Techniques and Applications (DICTA'11). pages: 209--216. 2011.

 @inproceedings{DICTA2011a,
   author    = "T. Wang and  X. He and  C. Shen and  N. Barnes",
   title     = "Laplacian margin distribution boosting for learning from sparsely labeled data",
   booktitle = "International Conference on Digital Image Computing: Techniques and Applications (DICTA'11)",
   pages     = "209--216",
   address   = "Queensland, Australia",
   year      = "2011",
 }

Graph mode-based contextual kernels for robust SVM tracking

X. Li, A. Dick, H. Wang, C. Shen, A. van den Hengel

Citation:
X. Li, A. Dick, H. Wang, C. Shen, A. van den Hengel. Graph mode-based contextual kernels for robust SVM tracking. IEEE International Conference on Computer Vision (ICCV'11). pages: 1156--1163. 2011.

 @inproceedings{ICCV2011,
   author    = "X. Li and  A. Dick and  H. Wang and  C. Shen and  A. van den Hengel",
   title     = "Graph mode-based contextual kernels for robust {SVM} tracking",
   booktitle = "IEEE International Conference on Computer Vision (ICCV'11)",
   pages     = "1156--1163",
   year      = "2011",
 }