Professor Javen Qinfeng Shi

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Citations	10173	7601
h-index	45	39
i10-index	98	91

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Anton van den HengelDirector of Applied Science at Amazon and Director of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
Chunhua ShenZhejiang UniversityVerified email at zju.edu.cn
Dong GongUniversity of New South Wales (UNSW)Verified email at unsw.edu.au
Ehsan AbbasnejadAustralian Institute for Machine Learning, University of AdelaideVerified email at adelaide.edu.au
Hamid RezatofighiAssistant Professor, Monash University, Melbourne, AustraliaVerified email at monash.edu
Ian D ReidMohammad Bin Zayed University of Artificial Intelligence and University of AdelaideVerified email at adelaide.edu.au
Qingsen YanNorthwestern Polytechnical UniversityVerified email at mail.nwpu.edu.cn
Zhen ZhangThe University of AdelaideVerified email at adelaide.edu.au
Julian McAuleyProfessor, UC San DiegoVerified email at eng.ucsd.edu
Lingqiao LiuAssociate Professor at the University of AdelaideVerified email at adelaide.edu.au
Mingkui TanSouth China University of TechnologyVerified email at scut.edu.cn
Damith C. RanasingheThe University of Adelaide, University of CambridgeVerified email at cs.adelaide.edu.au
Alex SmolaBoson AIVerified email at smola.org
Lei Zhang (NPU)Professor, Northwestern Polytechnical UniversityVerified email at nwpu.edu.cn
Anton MilanAmazonVerified email at amazon.com
Rui YaoPh.DVerified email at cumt.edu.cn
Anthony DickComputer Science, University of AdelaideVerified email at adelaide.edu.au
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityVerified email at stat.purdue.edu
Daniel CremersTechnical University of MunichVerified email at tum.de
Qi WuAssociate Professor, University of Adelaide, Adelaide, AustraliaVerified email at adelaide.edu.au

Professor Javen Qinfeng Shi

Director for Causal AI Group, University of Adelaide

Verified email at adelaide.edu.au - Homepage

Probabilistic Graphical Models Causation Counterfactuals 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	2212	2015
Mot20: A benchmark for multi object tracking in crowded scenes P Dendorfer, H Rezatofighi, A Milan, J Shi, D Cremers, I Reid, S Roth, ... arXiv preprint arXiv:2003.09003, 2020	499	2020
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	467	2014
Real-time visual tracking using compressive sensing H Li, C Shen, Q Shi CVPR 2011, 1305-1312, 2011	432	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	402	2015
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	399	2017
Is face recognition really a compressive sensing problem? Q Shi, A Eriksson, A Van Den Hengel, C Shen CVPR 2011, 553-560, 2011	356	2011
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	273	2009
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	268	2013
Attention-guided network for ghost-free high dynamic range imaging Q Yan, D Gong, Q Shi, A Hengel, C Shen, I Reid, Y Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	238	2019
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	238	2013
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	163	2015
COVID-19 chest CT image segmentation--a deep convolutional neural network solution Q Yan, B Wang, D Gong, C Luo, W Zhao, J Shen, Q Shi, S Jin, L Zhang, ... arXiv preprint arXiv:2004.10987, 2020	160	2020
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	153	2008
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	145	2018
Deep HDR imaging via a non-local network Q Yan, L Zhang, Y Liu, Y Zhu, J Sun, Q Shi, Y Zhang IEEE Transactions on Image Processing 29, 4308-4322, 2020	140	2020
Human action segmentation and recognition using discriminative semi-markov models Q Shi, L Cheng, L Wang, A Smola International journal of computer vision 93, 22-32, 2011	138	2011
Hash kernels Q Shi, J Petterson, G Dror, J Langford, A Smola, A Strehl, ... Artificial intelligence and statistics, 496-503, 2009	136	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	133	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	131	2013

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