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", }
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", }
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", }
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", }
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", }
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", }
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", }
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", }
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", }
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", }
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", }