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Refereed journal papers · 76

pdf	year	title	venue	authors
	’17	Structured learning of binary codes with column generation for optimizing ranking measures [...more]	IJCV	G. Lin, F. Liu, C. Shen, J. Wu, H. Shen
	’17	Removal of optically thick clouds from high-resolution satellite imagery using dictionary group learning and interdictionary nonlocal joint sparse coding	JSTAEORS	Y. Li, W. Li, C. Shen
	’17	Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition	PR	R. Qiao, L. Liu, C. Shen, A. van den Hengel
	’17	Deep linear discriminant analysis on Fisher networks: a hybrid architecture for person re-identification	PR	L. Wu, C. Shen, A. van den Hengel
	’17	Pushing the limits of deep CNNs for pedestrian detection	TCSVT	Q. Hu, P. Wang, C. Shen, A. van den Hengel, F. Porikli
	’17	Crowd counting via weighted VLAD on dense attribute feature maps	TCSVT	B. Sheng, C. Shen, G. Lin, J. Li, W. Yang, C. Sun
	’17	Discriminative training of deep fully-connected continuous CRF with task-specific loss	TIP	F. Liu, G. Lin, C. Shen
	’17	Exploiting depth from single monocular images for object detection and semantic segmentation	TIP	Y. Cao, C. Shen, H. Shen
	’17	Deep CNNs with spatially weighted pooling for fine-grained car recognition	TITS	Q. Hu, H. Wang, T. Li, C. Shen
	’17	Structured learning of tree potentials in CRF for image segmentation	TNN	F. Liu, G. Lin, R. Qiao, C. Shen
	’17	Exploring context with deep structured models for semantic segmentation	TPAMI	G. Lin, C. Shen, A. van den Hengel, I. Reid
	’17	Image captioning and visual question answering based on attributes and external knowledge	TPAMI	Q. Wu, C. Shen, A. van den Hengel, P. Wang, A. Dick
	’17	Compositional model based Fisher vector coding for image classification	TPAMI	L. Liu, P. Wang, C. Shen, L. Wang, A. van den Hengel, C. Wang, H. Shen
	’17	Cross-convolutional-layer pooling for image recognition	TPAMI	L. Liu, C. Shen, A. van den Hengel
	’16	Structured learning of metric ensembles with application to person re-identification	CVIU	S. Paisitkriangkrai, L. Wu, C. Shen, A. van den Hengel
	’16	Mining mid-level visual patterns with deep CNN activations [...more]	IJCV	Y. Li, L. Liu, C. Shen, A. van den Hengel
	’16	Efficient semidefinite branch-and-cut for MAP-MRF inference	IJCV	P. Wang, C. Shen, A. van den Hengel, P. Torr
	’16	Unsupervised feature learning for dense correspondences across scenes [...more]	IJCV	C. Zhang, C. Shen, T. Shen
	’16	Online unsupervised feature learning for visual tracking	IVC	F. Liu, C. Shen, I. Reid, A. van den Hengel
	’16	Canonical principal angles correlation analysis for two-view data	JVCIR	S. Wang, J. Lu, X. Gu, C. Shen, R. Xia, J. Yang
	’16	Face recognition using linear representation ensembles	PR	H. Li, F. Shen, C. Shen, Y. Yang, Y. Gao
	’16	Face image classification by pooling raw features [...more]	PR	F. Shen, C. Shen, X. Zhou, Y. Yang, H. Shen
	’16	Temporal pyramid pooling based convolutional neural network for action recognition	TCSVT	P. Wang, Y. Cao, C. Shen, L. Liu, H. Shen
	’16	Part-based robust tracking using online latent structured learning	TCSVT	R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel
	’16	Dictionary learning for promoting structured sparsity in hyerpsectral compressive sensing	TGRS	L. Zhang, W. Wei, Y. Zhang, C. Shen, A. van den Hengel, Q. Shi
	’16	Fast detection of multiple objects in traffic scenes with a common detection framework	TITS	Q. Hu, S. Paisitkriangkrai, C. Shen, A. van den Hengel, F. Porikli
	’16	Scalable linear visual feature learning via online parallel nonnegative matrix factorization	TNN	X. Zhao, X. Li, Z. Zhang, C. Shen, L. Gao, X. Li
	’16	Large-scale binary quadratic optimization using semidefinite relaxation and applications	TPAMI	P. Wang, C. Shen, A. van den Hengel, P. Torr
	’16	Learning depth from single monocular images using deep convolutional neural fields [...more]	TPAMI	F. Liu, C. Shen, G. Lin, I. Reid
	’16	Online metric-weighted linear representations for robust visual tracking	TPAMI	X. Li, C. Shen, A. Dick, Z. Zhang, Y. Zhuang
	’16	Pedestrian detection with spatially pooled features and structured ensemble learning [...more]	TPAMI	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’16	A generalized probabilistic framework for compact codebook creation	TPAMI	L. Liu, L. Wang, C. Shen
	’15	Extrinsic methods for coding and dictionary learning on Grassmann manifolds [...more]	IJCV	M. Harandi, R. Hartley, C. Shen, B. Lovell, C. Sanderson
	’15	CRF learning with CNN features for image segmentation	PR	F. Liu, G. Lin, C. Shen
	’15	Hashing on nonlinear manifolds [...more]	TIP	F. Shen, C. Shen, Q. Shi, A. van den Hengel, Z. Tang, H. Shen
	’15	Worst-case linear discriminant analysis as scalable semidefinite feasibility problems [...more]	TIP	H. Li, C. Shen, A. van den Hengel, Q. Shi
	’15	A computational model of the short-cut rule for 2D shape decomposition	TIP	L. Luo, C. Shen, X. Liu, C. Zhang
	’15	Supervised hashing using graph cuts and boosted decision trees [...more]	TPAMI	G. Lin, C. Shen, A. van den Hengel
	’14	Fast approximate \(l_\infty\) minimization: Speeding up robust regression	CSDA	F. Shen, C. Shen, R. Hill, A. van den Hengel, Z. Tang
	’14	Multiple kernel learning in the primal for multi-modal Alzheimer's disease classification	JBHI	F. Liu, L. Zhou, C. Shen, J. Yin
	’14	Multiple kernel clustering based on centered kernel alignment	PR	Y. Lu, L. Wang, J. Lu, J. Yang, C. Shen
	’14	Large-margin learning of compact binary image encodings	TIP	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’14	Efficient semidefinite spectral clustering via Lagrange duality	TIP	Y. Yan, C. Shen, H. Wang
	’14	Characterness: An indicator of text in the wild [...more]	TIP	Y. Li, W. Jia, C. Shen, A. van den Hengel
	’14	Context-aware hypergraph construction for robust spectral clustering	TKDE	X. Li, W. Hu, C. Shen, A. Dick, Z. Zhang
	’14	Asymmetric pruning for learning cascade detectors	TMM	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’14	Efficient dual approach to distance metric learning	TNN	C. Shen, J. Kim, F. Liu, L. Wang, A. van den Hengel
	’14	A scalable stage-wise approach to large-margin multi-class loss based boosting	TNN	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’14	RandomBoost: Simplified multi-class boosting through randomization	TNN	S. Paisitkriangkrai, C. Shen, Q. Shi, A. van den Hengel
	’14	StructBoost: Boosting methods for predicting structured output variables	TPAMI	C. Shen, G. Lin, A. van den Hengel
	’14	A hierarchical word-merging algorithm with class separability measure	TPAMI	L. Wang, L. Zhou, C. Shen, L. Liu, H. Liu
	’13	Training effective node classifiers for cascade classification [...more]	IJCV	C. Shen, P. Wang, S. Paisitkriangkrai, A. van den Hengel
	’13	Fully corrective boosting with arbitrary loss and regularization	NN	C. Shen, H. Li, A. van den Hengel
	’13	Visual tracking with spatio-temporal Dempster-Shafer information fusion	TIP	X. Li, A. Dick, C. Shen, Z. Zhang, A. van den Hengel, H. Wang
	’13	Approximate least trimmed sum of squares fitting and applications in image analysis	TIP	F. Shen, C. Shen, A. van den Hengel, Z. Tang
	’13	A survey of appearance models in visual object tracking	TIST	X. Li, W. Hu, C. Shen, Z. Zhang, A. Dick, A. van den Hengel
	’13	Shape similarity analysis by self-tuning locally constrained mixed-diffusion	TMM	L. Luo, C. Shen, C. Zhang, A. van den Hengel
	’13	Incremental learning of 3D-DCT compact representations for robust visual tracking [...more]	TPAMI	X. Li, A. Dick, C. Shen, A. van den Hengel, H. Wang
	’12	Positive semidefinite metric learning using boosting-like algorithms [...more]	JMLR	C. Shen, J. Kim, L. Wang, A. van den Hengel
	’12	Fast and robust object detection using asymmetric totally-corrective boosting	TNN	P. Wang, C. Shen, N. Barnes, H. Zheng
	’12	UBoost: Boosting with the Universum	TPAMI	C. Shen, P. Wang, F. Shen, H. Wang
	’11	Efficiently learning a detection cascade with sparse eigenvectors	TIP	C. Shen, S. Paisitkriangkrai, J. Zhang
	’11	Incremental training of a detector using online sparse eigen-decomposition	TIP	S. Paisitkriangkrai, C. Shen, J. Zhang
	’10	Interactive color image segmentation with linear programming	MVA	H. Li, C. Shen
	’10	Generalized kernel-based visual tracking [...more]	TCSVT	C. Shen, J. Kim, H. Wang
	’10	Scalable large-margin Mahalanobis distance metric learning	TNN	C. Shen, J. Kim, L. Wang
	’10	Feature selection with redundancy-constrained class separability	TNN	L. Zhou, L. Wang, C. Shen
	’10	Boosting through optimization of margin distributions	TNN	C. Shen, H. Li
	’10	On the dual formulation of boosting algorithms	TPAMI	C. Shen, H. Li
	’08	Performance evaluation of local features in human classification and detection	IETCV	S. Paisitkriangkrai, C. Shen, J. Zhang
	’08	Supervised dimensionality reduction via sequential semidefinite programming	PR	C. Shen, H. Li, M. Brooks
	’08	Fast pedestrian detection using a cascade of boosted covariance features	TCSVT	S. Paisitkriangkrai, C. Shen, J. Zhang
	’07	Fast global kernel density mode seeking: applications to localization and tracking	TIP	C. Shen, M. Brooks, A. van den Hengel
	’07	Adaptive object tracking based on an effective appearance filter	TPAMI	H. Wang, D. Suter, K. Schindler, C. Shen
	’04	Active control of radiation from a piston set in a rigid sphere	JASA	Z. Lin, J. Lu, C. Shen, X. Qiu, B. Xu
	’03	Lattice form adaptive infinite impulse response filtering algorithm for active noise control	JASA	J. Lu, C. Shen, X. Qiu, B. Xu

Refereed conference papers · 107

pdf	year	title	venue	authors
	’17	Visually aligned word embeddings for improving zero-shot learning	BMVC	R. Qiao, L. Liu, C. Shen, A. van den Hengel
	’17	Weakly supervised semantic segmentation based on co-segmentation	BMVC	T. Shen, G. Lin, L. Liu, C. Shen, I. Reid
	’17	The VQA-machine: learning how to use existing vision algorithms to answer new questions	CVPR	P. Wang, Q. Wu, C. Shen, A. van den Hengel
	’17	RefineNet: multi-path refinement networks for high-resolution semantic segmentation [...more]	CVPR	G. Lin, A. Milan, C. Shen, I. Reid
	’17	Sequential person recognition in photo albums with a recurrent network	CVPR	Y. Li, G. Lin, B. Zhuang, L. Liu, C. Shen, A. van den Hengel
	’17	From motion blur to motion flow: a deep learning solution for removing heterogeneous motion blur	CVPR	D. Gong, J. Yang, L. Liu, Y. Zhang, I. Reid, C. Shen, A. van den Hengel, Q. Shi
	’17	Attend in groups: a weakly-supervised deep learning framework for learning from web data	CVPR	B. Zhuang, L. Liu, C. Shen, I. Reid
	’17	Multi-attention network for one shot learning	CVPR	P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, H. Shen
	’17	When unsupervised domain adaptation meets tensor representations	ICCV	H. Lu, L. Zhang, Z. Cao, W. Wei, K. Xian, C. Shen, A. van den Hengel
	’17	Towards context-aware interaction recognition	ICCV	B. Zhuang, L. Liu, C. Shen, I. Reid
	’17	Adversarial PoseNet: a structure-aware convolutional network for human pose estimation	ICCV	Y. Chen, C. Shen, X. Wei, L. Liu, J. Yang
	’17	Semi-global weighted least squares in image filtering	ICCV	W. Liu, X. Chen, C. Shen, Z. Liu, J. Yang
	’17	Towards end-to-end text spotting with convolutional recurrent neural networks	ICCV	H. Li, P. Wang, C. Shen
	’17	Learning multi-level region consistency with dense multi-label networks for semantic segmentation	IJCAI	T. Shen, G. Lin, C. Shen, I. Reid
	’17	Deep descriptor transforming for image co-localization	IJCAI	X. Wei, C. Zhang, Y. Li, C. Xie, J. Wu, C. Shen, Z. Zhou
	’17	Explicit knowledge-based reasoning for visual question answering	IJCAI	P. Wang, Q. Wu, C. Shen, A. van den Hengel, A. Dick
	’16	Ask me anything: free-form visual question answering based on knowledge from external sources	CVPR	Q. Wu, P. Wang, C. Shen, A. Dick, A. van den Hengel
	’16	What value do explicit high level concepts have in vision to language problems	CVPR	Q. Wu, C. Shen, L. Liu, A. Dick, A. van den Hengel
	’16	What's wrong with that object? identifying irregular object from images by modelling the detection score distribution	CVPR	P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, H. Shen
	’16	Efficient piecewise training of deep structured models for semantic segmentation	CVPR	G. Lin, C. Shen, A. van dan Hengel, I. Reid
	’16	Fast training of triplet-based deep binary embedding networks [...more]	CVPR	B. Zhuang, G. Lin, C. Shen, I. Reid
	’16	Less is more: zero-shot learning from online textual documents with noise suppression	CVPR	R. Qiao, L. Liu, C. Shen, A. van den Hengel
	’16	Cluster sparsity field for hyperspectral imagery denoising	ECCV	L. Zhang, W. Wei, Y. Zhang, C. Shen, A. van den Hengel, Q. Shi
	’16	Image co-localization by mimicking a good detector's confidence score distribution	ECCV	Y. Li, L. Liu, C. Shen, A. van den Hengel
	’16	Image restoration using very deep fully convolutional encoder-decoder networks with symmetric skip connections [...more]	NIPS	X. Mao, C. Shen, Y. Yang
	’15	Mid-level deep pattern mining [...more]	CVPR	Y. Li, L. Liu, C. Shen, A. van den Hengel
	’15	Deep convolutional neural fields for depth estimation from a single image [...more]	CVPR	F. Liu, C. Shen, G. Lin
	’15	Supervised discrete hashing [...more]	CVPR	F. Shen, C. Shen, W. Liu, H. Shen
	’15	The treasure beneath convolutional layers: cross convolutional layer pooling for image classification	CVPR	L. Liu, C. Shen, A. van den Hengel
	’15	Efficient SDP inference for fully-connected CRFs based on low-rank decomposition	CVPR	P. Wang, C. Shen, A. van den Hengel
	’15	Learning to rank in person re-identification with metric ensembles	CVPR	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’15	Learning graph structure for multi-label image classification via clique generation	CVPR	M. Tan, Q. Shi, A. van den Hengel, C. Shen, J. Gao, F. Hu, Z. Zhang
	’15	Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs	CVPR	B. Li, C. Shen, Y. Dai, A. van den Hengel, M. He
	’15	Hyperspectral compressive sensing using manifold-structured sparsity prior	ICCV	L. Zhang, W. Wei, Y. Zhang, F. Li, C. Shen, Q. Shi
	’15	Deeply learning the messages in message passing inference	NIPS	G. Lin, C. Shen, I. Reid, A. van den Hengel
	’15	Sequence searching with deep-learnt depth for condition- and viewpoint-invariant route-based place recognition	workshop	M. Milford, C. Shen, S. Lowry, N. Suenderhauf, S. Shirazi, G. Lin, F. Liu, E. Pepperell, C. Lerma, B. Upcroft, I. Reid
	’14	Fast supervised hashing with decision trees for high-dimensional data [...more]	CVPR	G. Lin, C. Shen, Q. Shi, A. van den Hengel, D. Suter
	’14	Optimizing ranking measures for compact binary code learning [...more]	ECCV	G. Lin, C. Shen, J. Wu
	’14	Strengthening the effectiveness of pedestrian detection with spatially pooled features [...more]	ECCV	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’14	Encoding high dimensional local features by sparse coding based Fisher vectors	NIPS	L. Liu, C. Shen, L. Wang, A. van den Hengel, C. Wang
	’13	Inductive hashing on manifolds [...more]	CVPR	F. Shen, C. Shen, Q. Shi, A. van den Hengel, Z. Tang
	’13	Learning compact binary codes for visual tracking	CVPR	X. Li, C. Shen, A. Dick, A. van den Hengel
	’13	Bilinear programming for human activity recognition with unknown MRF graphs	CVPR	Z. Wang, Q. Shi, C. Shen, A. van den Hengel
	’13	A fast semidefinite approach to solving binary quadratic problems [...more]	CVPR	P. Wang, C. Shen, A. van den Hengel
	’13	Part-based visual tracking with online latent structural learning [...more]	CVPR	R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel
	’13	A general two-step approach to learning-based hashing [...more]	ICCV	G. Lin, C. Shen, D. Suter, A. van den Hengel
	’13	Efficient pedestrian detection by directly optimizing the partial area under the ROC curve	ICCV	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’13	Contextual hypergraph modeling for salient object detection [...more]	ICCV	X. Li, Y. Li, C. Shen, A. Dick, A. van den Hengel
	’13	Dictionary learning and sparse coding on Grassmann manifolds: an extrinsic solution [...more]	ICCV	M. Harandi, C. Sanderson, C. Shen, B. Lovell
	’13	Approximate constraint generation for efficient structured boosting	ICIP	G. Lin, C. Shen, A. van den Hengel
	’13	Leveraging surrounding context for scene text detection	ICIP	Y. Li, C. Shen, W. Jia, A. van den Hengel
	’13	Extended depth-of-field via focus stacking and graph cuts	ICIP	C. Zhang, J. Bastian, C. Shen, A. van den Hengel, T. Shen
	’13	Learning hash functions using column generation [...more]	ICML	X. Li, G. Lin, C. Shen, A. van den Hengel, A. Dick
	’12	Fast training of effective multi-class boosting using coordinate descent optimization	ACCV	G. Lin, C. Shen, A. van den Hengel, D. Suter
	’12	Non-sparse linear representations for visual tracking with online reservoir metric learning	CVPR	X. Li, C. Shen, Q. Shi, A. Dick, A. van den Hengel
	’12	Sharing features in multi-class boosting via group sparsity	CVPR	S. Paisitkriangkrai, C. Shen, A. van den Hengel
	’12	Robust tracking with weighted online structured learning	ECCV	R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel
	’12	Is margin preserved after random projection?	ICML	Q. Shi, C. Shen, R. Hill, A. van den Hengel
	’11	Efficiently learning a distance metric for large margin nearest neighbor classification	AAAI	K. Park, C. Shen, Z. Hao, J. Kim
	’11	A direct formulation for totally-corrective multi-class boosting	CVPR	C. Shen, Z. Hao
	’11	A generalized probabilistic framework for compact codebook creation	CVPR	L. Liu, L. Wang, C. Shen
	’11	Is face recognition really a compressive sensing problem?	CVPR	Q. Shi, A. Eriksson, A. van den Hengel, C. Shen
	’11	Real-time visual tracking using compressive sensing	CVPR	H. Li, C. Shen, Q. Shi
	’11	A scalable dual approach to semidefinite metric learning	CVPR	C. Shen, J. Kim, L. Wang
	’11	On the optimality of sequential forward feature selection using class separability measure	DICTA	L. Wang, C. Shen, R. Hartley
	’11	Laplacian margin distribution boosting for learning from sparsely labeled data	DICTA	T. Wang, X. He, C. Shen, N. Barnes
	’11	Graph mode-based contextual kernels for robust SVM tracking	ICCV	X. Li, A. Dick, H. Wang, C. Shen, A. van den Hengel
	’10	Asymmetric totally-corrective boosting for real-time object detection	ACCV	P. Wang, C. Shen, N. Barnes, H. Zheng, Z. Ren
	’10	Pyramid center-symmetric local binary, trinary patterns for effective pedestrian detection	ACCV	Y. Zheng, C. Shen, R. Hartley, X. Huang
	’10	Totally-corrective multi-class boosting	ACCV	Z. Hao, C. Shen, N. Barnes, B. Wang
	’10	Face detection with effective feature extraction	ACCV	S. Paisitkriangkrai, C. Shen, J. Zhang
	’10	Rapid face recognition using hashing	CVPR	Q. Shi, H. Li, C. Shen
	’10	Robust face recognition via accurate face alignment and sparse representation	DICTA	H. Li, P. Wang, C. Shen
	’10	LACBoost and FisherBoost: optimally building cascade classifiers	ECCV	C. Shen, P. Wang, H. Li
	’10	Improved human detection and classification in thermal images	ICIP	W. Wang, J. Zhang, C. Shen
	’10	Training a multi-exit cascade with linear asymmetric classification for efficient object detection	ICIP	P. Wang, C. Shen, H. Zheng, Z. Ren
	’10	Hippocampal shape classification using redundancy constrained feature selection	MICCAI	L. Zhou, L. Wang, C. Shen, N. Barnes
	’09	A variant of the trace quotient formulation for dimensionality reduction	ACCV	P. Wang, C. Shen, H. Zheng, Z. Ren
	’09	A scalable algorithm for learning a Mahalanobis distance metric	ACCV	J. Kim, C. Shen, L. Wang
	’09	Efficiently training a better visual detector with sparse eigenvectors	CVPR	S. Paisitkriangkrai, C. Shen, J. Zhang
	’09	Smooth approximation of \(l_\infty\)-norm for multi-view geometry	DICTA	Y. Dai, H. Li, M. He, C. Shen
	’09	A two-layer night-time vehicle detector	DICTA	W. Wang, C. Shen, J. Zhang, S. Paisitkriangkrai
	’09	Positive semidefinite metric learning with boosting [...more]	NIPS	C. Shen, J. Kim, L. Wang, A. van den Hengel
	’08	Multi-view human motion capture with an improved deformation skin model	DICTA	Y. Lu, L. Wang, R. Hartley, H. Li, C. Shen
	’08	Learning cascaded reduced-set SVMs using linear programming	DICTA	J. Kim, C. Shen, L. Wang
	’08	Boosting the minimum margin: LPBoost vs. AdaBoost	DICTA	H. Li, C. Shen
	’08	Self-calibrating cameras using semidefinite programming	DICTA	C. Shen, H. Li, M. Brooks
	’08	A fast algorithm for creating a compact and discriminative visual codebook	ECCV	L. Wang, L. Zhou, C. Shen
	’08	Face detection from few training examples	ICIP	C. Shen, S. Paisitkriangkrai, J. Zhang
	’08	PSDBoost: matrix-generation linear programming for positive semidefinite matrices learning	NIPS	C. Shen, A. Welsh, L. Wang
	’08	Real-time pedestrian detection using a boosted multi-layer classifier	workshop	S. Paisitkriangkrai, C. Shen, J. Zhang
	’07	A convex programming approach to the trace quotient problem	ACCV	C. Shen, H. Li, M. Brooks
	’07	Kernel-based tracking from a probabilistic viewpoint	CVPR	Q. Nguyen, A. Robles-Kelly, C. Shen
	’07	Color image labelling using linear programming	DICTA	H. Li, C. Shen, Z. Wen
	’07	An experimental evaluation of local features for pedestrian classification	DICTA	S. Paisitkriangkrai, C. Shen, J. Zhang
	’07	Feature extraction using sequential semidefinite programming	DICTA	C. Shen, H. Li, M. Brooks
	’07	Object-respecting colour image segmentation: an LP approach	ICIP	H. Li, C. Shen
	’06	Classification-based likelihood functions for Bayesian tracking	AVSS	C. Shen, H. Li, M. Brooks
	’06	An LMI approach for reliable PTZ camera self-calibration	AVSS	H. Li, C. Shen
	’06	Enhanced kernel-based tracking for monochromatic and thermographic video	AVSS	Q. Nguyen, A. Robles-Kelly, C. Shen
	’05	Fast global kernel density mode seeking with application to localisation and tracking	ICCV	C. Shen, M. Brooks, A. van den Hengel
	’05	Visual tracking via efficient kernel discriminant subspace learning	ICIP	C. Shen, A. van den Hengel, M. Brooks
	’05	Augmented particle filtering for efficient visual tracking	ICIP	C. Shen, M. Brooks, A. van den Hengel
	’05	Adaptive over-relaxed mean shift	ISSPA	C. Shen, M. Brooks
	’04	Enhanced importance sampling: unscented auxiliary particle filtering for visual tracking	AI	C. Shen, A. van den Hengel, A. Dick, M. Brooks
	’04	2D articulated tracking with dynamic Bayesian networks	CIT	C. Shen, A. van den Hengel, A. Dick, M. Brooks
	’03	Probabilistic multiple cue integration for particle filter based tracking	DICTA	C. Shen, A. van den Hengel, A. Dick

Other papers · 2

type	year	title	venue	authors
	’12	Semidefinite programming (book chapter in: encyclopedia of computer vision, springer)	book	C. Shen, A. van den Hengel
	’10	Proceedings of international conference on digital image computing: techniques and applications	book	J. Zhang, C. Shen, G. Geers, Q. Wu