Professor Javen Qinfeng Shi

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Anton van den HengelDirector, Australian Institute for Machine Learning, UoA | Director of Applied Science, AmazonVerified email at adelaide.edu.au
Chunhua ShenSchool of Computer Science, The University of AdelaideVerified email at adelaide.edu.au
Ian D ReidUniversity of AdelaideVerified email at adelaide.edu.au
Hamid RezatofighiAssistant Professor, Monash University, Melbourne, AustraliaVerified email at monash.edu
Mingkui TanSouth China University of TechnologyVerified email at scut.edu.cn
Zhen ZhangThe University of AdelaideVerified email at adelaide.edu.au
Julian McAuleyProfessor, UC San DiegoVerified email at eng.ucsd.edu
Alex SmolaAmazon Web ServicesVerified email at smola.org
Damith C. RanasingheThe University of Adelaide, University of CambridgeVerified email at cs.adelaide.edu.au
Rui YaoPh.DVerified email at adelaide.edu.au
Anthony DickComputer Science, University of AdelaideVerified email at adelaide.edu.au
Lei Zhang (NPU)Professor, Northwestern Polytechnical UniversityVerified email at nwpu.edu.cn
Professor Junbin GaoDiscipline of Business Analytics in Business School, The University of SydneyVerified email at sydney.edu.au
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityVerified email at stat.purdue.edu
Anton Milan (Andriyenko)AmazonVerified email at amazon.com
Guosheng LinNanyang Technological UniversityVerified email at ntu.edu.sg
Lingqiao LiuSenior Lecturer of the University of AdelaideVerified email at adelaide.edu.au
Ehsan AbbasnejadAustralian Institute for Machine Learning, University of AdelaideVerified email at adelaide.edu.au
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Roberto L. Shinmoto TorresThe University of AdelaideVerified email at adelaide.edu.au

Professor Javen Qinfeng Shi

Director for Probabilistic Graphical Model Group, UoA | DeepSightX | Smarter Regions

Verified email at adelaide.edu.au - Homepage

Probabilistic Graphical Models Counterfactuals Causality Machine Learning Computer Vision


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Image-based recommendations on styles and substitutes J McAuley, C Targett, Q Shi, A Van Den Hengel Proceedings of the 38th international ACM SIGIR conference on research and …, 2015	1225	2015
Real-time visual tracking using compressive sensing H Li, C Shen, Q Shi CVPR 2011, 1305-1312, 2011	412	2011
Fast supervised hashing with decision trees for high-dimensional data G Lin, C Shen, Q Shi, A Van den Hengel, D Suter Proceedings of the IEEE conference on computer vision and pattern …, 2014	404	2014
Is face recognition really a compressive sensing problem? Q Shi, A Eriksson, A Van Den Hengel, C Shen CVPR 2011, 553-560, 2011	337	2011
Joint probabilistic data association revisited SH Rezatofighi, A Milan, Z Zhang, Q Shi, A Dick, I Reid Proceedings of the IEEE international conference on computer vision, 3047-3055, 2015	286	2015
Inductive Hashing on Manifolds F Shen, C Shen, Q Shi, A Hengel, Z Tang IEEE Conference on Computer Vision and Pattern Recognition (26th: 2013 …, 2013	239	2013
Hash kernels for structured data. Q Shi, J Petterson, G Dror, J Langford, A Smola, SVN Vishwanathan Journal of Machine Learning Research 10 (11), 2009	231	2009
Part-based visual tracking with online latent structural learning R Yao, Q Shi, C Shen, Y Zhang, A Van Den Hengel Proceedings of the IEEE conference on computer vision and pattern …, 2013	221	2013
From motion blur to motion flow: A deep learning solution for removing heterogeneous motion blur D Gong, J Yang, L Liu, Y Zhang, I Reid, C Shen, A Van Den Hengel, Q Shi Proceedings of the IEEE conference on computer vision and pattern …, 2017	210	2017
Discriminative human action segmentation and recognition using semi-Markov model Q Shi, L Wang, L Cheng, A Smola 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008	151	2008
Hashing on nonlinear manifolds F Shen, C Shen, Q Shi, A Van den Hengel, Z Tang, HT Shen IEEE Transactions on Image Processing 24 (6), 1839-1851, 2015	149	2015
Human action segmentation and recognition using discriminative semi-markov models Q Shi, L Cheng, L Wang, A Smola International journal of computer vision 93 (1), 22-32, 2011	123	2011
Hash kernels Q Shi, J Petterson, G Dror, J Langford, A Smola, A Strehl, ... Artificial intelligence and statistics, 496-503, 2009	121	2009
Dual graph regularized latent low-rank representation for subspace clustering M Yin, J Gao, Z Lin, Q Shi, Y Guo IEEE Transactions on Image Processing 24 (12), 4918-4933, 2015	106	2015
Sensor enabled wearable RFID technology for mitigating the risk of falls near beds RLS Torres, DC Ranasinghe, Q Shi, AP Sample 2013 IEEE international conference on RFID (RFID), 191-198, 2013	89	2013
Non-sparse linear representations for visual tracking with online reservoir metric learning X Li, C Shen, Q Shi, A Dick, A Van Den Hengel 2012 IEEE Conference on Computer Vision and Pattern Recognition, 1760-1767, 2012	80	2012
Seeing deeply and bidirectionally: A deep learning approach for single image reflection removal J Yang, D Gong, L Liu, Q Shi Proceedings of the european conference on computer vision (ECCV), 654-669, 2018	70	2018
Cluster sparsity field: An internal hyperspectral imagery prior for reconstruction L Zhang, W Wei, Y Zhang, C Shen, A Van Den Hengel, Q Shi International Journal of Computer Vision 126 (8), 797-821, 2018	62	2018
Blind image deconvolution by automatic gradient activation D Gong, M Tan, Y Zhang, A Van den Hengel, Q Shi Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016	61	2016
Is margin preserved after random projection? Q Shi, C Shen, R Hill, A Hengel The 29th International Conference on Machine Learning (ICML 12), Edinburgh …, 2012	61	2012

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