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Selected journal papers

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	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	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	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	Supervised hashing using graph cuts and boosted decision trees [...more]	TPAMI	G. Lin, C. Shen, 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	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	UBoost: Boosting with the Universum	TPAMI	C. Shen, P. Wang, F. Shen, H. Wang
	’10	On the dual formulation of boosting algorithms	TPAMI	C. Shen, H. Li
	’07	Adaptive object tracking based on an effective appearance filter	TPAMI	H. Wang, D. Suter, K. Schindler, C. Shen

Selected conference papers

pdf	year	title	venue	authors
	’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
	’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
	’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	Learning hash functions using column generation [...more]	ICML	X. Li, G. Lin, C. Shen, A. van den Hengel, A. Dick
	’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	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	Graph mode-based contextual kernels for robust SVM tracking	ICCV	X. Li, A. Dick, H. Wang, C. Shen, A. van den Hengel
	’10	Rapid face recognition using hashing	CVPR	Q. Shi, H. Li, C. Shen
	’10	LACBoost and FisherBoost: optimally building cascade classifiers	ECCV	C. Shen, P. Wang, H. Li
	’09	Efficiently training a better visual detector with sparse eigenvectors	CVPR	S. Paisitkriangkrai, C. Shen, J. Zhang
	’09	Positive semidefinite metric learning with boosting [...more]	NIPS	C. Shen, J. Kim, L. Wang, A. van den Hengel
	’08	A fast algorithm for creating a compact and discriminative visual codebook	ECCV	L. Wang, L. Zhou, C. Shen
	’08	PSDBoost: matrix-generation linear programming for positive semidefinite matrices learning	NIPS	C. Shen, A. Welsh, L. Wang
	’07	Kernel-based tracking from a probabilistic viewpoint	CVPR	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