Publications (selected)
| 100 |
 Liu Y, Zhang Z, Gong D, Gong M, Huang B, Hengel AVD, Zhang K, Shi JQ,
Identifiable Latent Polynomial Causal Models Through the Lens of Change,
ICLR 2024.
|
| 99 |
Yan Q, Fruzangohar M, Taylor J, Gong D, Walter J, Norman A, Shi JQ, Coram T,
Improved genomic prediction using machine learning with Variational Bayesian sparsity,
Plant Methods 2023.
|
| 98 |
Zhao Y, Li H, Shan J, Zhang Z, Li X, Shi JQ, Jiao Y, Li H,
Machine Learning Confirms the Formation Mechanism of a Single-Atom Catalyst via Infrared Spectroscopic Analysis,
Journal of Physical Chemistry Letters 2023.
|
| 97 |
Yuwono JA, Li X, Dolezal TD, Samin AJ, Shi JQ, Li Z, Birbilis N,
A computational approach for mapping electrochemical activity of multi-principal element alloys,
Materials Degradation 2023.
|
| 96 |
Li X, Shi JQ, Page AJ,
Discovery of Graphene Growth Alloy Catalysts Using High-Throughput Machine Learning,
Nano Letters 2023.
|
| 95 |
Zhang Z, Dupty MH, Wu F, Shi JQ, Lee WS,
Factor Graph Neural Networks,
Journal of Machine Learning Research 2023.
|
| 94 |
Meng J, Wang Z, Ying K, Zhang J, Guo D, Zhang Z, Shi JQ, Chen S,
Human Interaction Understanding with Consistency-Aware Learning,
IEEE Transactions on Pattern Analysis and Machine Intelligence 2023.
|
| 93 |
Li X, Li H, Zhang Z, Shi JQ, Jiao Y, Qiao SZ,
Active-learning accelerated computational screening of A2B@NG catalysts for CO2 electrochemical reduction,
Nano Energy 2023.
|
| 92 |
Yan Q, Liu S, Xu S, Dong C, Li Z, Shi JQ, Zhang Y, Dai D,
3D Medical image segmentation using parallel transformers,
Pattern Recognition 2023.
|
| 91 |
Yan Q, Gong D, Wang P, Zhang Z, Zhang Y, Shi JQ,
SharpFormer: Learning Local Feature Preserving Global Representations for Image Deblurring,
IEEE Transactions on Image Processing 2023.
|
| 90 |
Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan M Abbasnejad, Mingming Gong, Kun Zhang, Javen Qingfeng Shi,
Truncated Matrix Power Iteration for Differentiable DAG Learning,
NeurIPS 2022.
|
| 89 |
Bao Gia Doan, Ehsan Abbasnejad, Javen Qinfeng Shi, Damith Ranashinghe,
Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense,
ICML 2022.
|
| 88 |
Amin Parvaneh, Ehsan Abbasnejad, Damien.Teney, Gholamreza Haffari, Anton van den Hengel,
Javen Qinfeng Shi,
Active Learning by Feature Mixing,
CVPR 2022.
|
| 87 |
Xinyu Zhang etc.
Implicit Sample Extension for Unsupervised Person Re-Identification,
CVPR, 2022.
|
| 86 |
Qingsen Yan, Dong Gong, Yuhang Liu, Anton van den Hengel,
Javen Qinfeng Shi,
Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning,
CVPR, 2022.
|
| 85 |
Zhenhua Wang, Jiajun Meng, Dongyan Guo, Jianhua Zhang, Javen Qinfeng Shi, Shengyong Chen,
Consistency-Aware Graph Network for Human Interaction Understanding,
ICCV (oral), 2021.
|
| 84 |
Dong Gong, Zhen Zhang, Javen Qinfeng Shi, Anton van den Hengel,
Memory-augmented Dynamic Neural Relational Inference,
ICCV, 2021.
|
| 83 |
Rezatofighi, H., Zhu, T., Kaskman, R., Motlagh, F. T., Shi, Q., Milan, A., Cremers, D., Leal-Taixe, L. & Reid, I. D.,
Learn to predict sets using feed-forward neural networks,
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
|
| 82 |
Alireza Abedin, Mahsa Ehsanpour, Qinfeng Shi, Hamid Rezatofighi, Damith C. Ranasinghe,
Attend and Discriminate: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors,
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021.
|
| 81 |
Qingsen Yan, Bo Wang, Dong Gong, Chuan Luo, Wei Zhao, Jianhu Shen, Jingyang Ai, Qinfeng Shi, Yanning Zhang, Shuo Jin, Liang Zhang, Zheng You,
COVID-19 Chest CT Image Segmentation Network by Multi-Scale Fusion and Enhancement Operations,
IEEE Trans. Big Data, 2021.
|
| 80 |
Qingsen Yan, Bo Wang, Wei Zhang, Chuan Luo, Wei Xu, Zhengqing Xu, Yanning Zhang, Qinfeng Shi, Liang Zhang, Zheng You,
Attention-Guided Deep Neural Network With Multi-Scale Feature Fusion for Liver Vessel Segmentation,
IEEE J. Biomed. Health Informatics, 2021.
|
| 79 |
Yinglong Wang, Dong Gong, Jie Yang, Qinfeng Shi, Anton van den Hengel, Dehua Xie, Bing Zeng,
Deep Single Image Deraining via Modeling Haze-Like Effect,
IEEE Trans. Multim, 2021.
|
| 78 |
Mohammad Mahdi Kazemi Moghaddam, Qi Wu, Ehsan Abbasnejad, Javen Shi,
Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation,
WACV, 2021.
|
| 77 |
Sun W, Gong D, Shi Q, van den Hengel A, Zhang Y.,
Learning to Zoom-in via Learning to Zoom-out: Real-world Super-resolution by Generating and Adapting Degradation,
IEEE Transactions on Image Processing, 2021.
|
| 76 |
Zhang L, Wei W, Shi Q, Shen C, van den Hengel A, Zhang Y.,
Accurate Tensor Completion via Adaptive Low-Rank Representation,
IEEE transactions on neural networks and learning systems, 2020.
|
| 75 |
Yan Q, Zhang L, Liu Y, Zhu Y, Sun J, Shi Q, Zhang Y.,
Deep HDR imaging via A non-local network,
IEEE Transactions on Image Processing, 2020.
|
| 74 |
Guo Y, Chen J, Du Q, Van Den Hengel A, Shi Q, Tan M.,
Multi-way backpropagation for training compact deep neural networks,
Neural Networks, 2020.
|
| 73 |
Gong D, Zhang Z, Shi Q, van den Hengel A, Shen C, Zhang Y.,
Learning deep gradient descent optimization for image deconvolution,
IEEE Transactions on Neural Networks and Learning Systems, 2020.
|
| 72 |
Parvaneh A, Abbasnejad M, Teney D, Shi Q, Van Den Hengel A.,
Counterfactual Vision-and-Language Navigation: Unravelling the Unseen,
NeurIPS, 2020.
|
| 71 |
Abbasnejad M, Abbasnejad I, Wu Q, Shi Q, Van Den Hengel A.,
Gold Seeker: Information Gain from Policy Distributions for Goal-oriented Vision-and-Langauge Reasoning,
CVPR, 2020.
|
| 70 |
Abbasnejad M, Teney D, Parvaneh A, Shi Q, Van Den Hengel A.,
Counterfactual Vision and Language Learning,
CVPR, 2020.
|
| 69 |
Yan Y, Tan M, Tsang I, Yang Y, Shi Q, Zhang C,
Fast and Low Memory Cost Matrix Factorization: Algorithm, Analysis and Case Study,
IEEE Transactions on Knowledge and Data Engineering, 2020.
|
| 68 |
Yan Q, Zhang L, Liu Y, Zhu Y, Sun J, Shi Q, Zhang Y,
Deep HDR Imaging via A Non-local Network,
IEEE Transactions on Image Processing, 2020.
|
| 67 |
Zhang L, Wei W, Shi Q, Shen C, van den Hengel A, Zhang Y,
Accurate Tensor Completion via Adaptive Low-Rank Representation,
IEEE Transactions on Neural Networks and Learning Systems, 2019.
|
| 66 |
Zhenhua Wang etal,
New Convex Relaxations for MRF Inference with Unknown Graphs,
ICCV, 2019.
|
| 65 |
Chongyu Liu, Rui Yao, Hamid Rezatofighi, Qinfeng Shi,
Model-free tracker for multiple objects using joint appearance and motion inference,
TIP, 2019.
|
| 64 |
Suwanwimolkul S, Zhang L, Ranasinghe D, Shi Q,
One-step adaptive Markov random field for structured compressive sensing,
Signal Processing, 2019.
|
| 63 |
Gong D, Tan M, Shi Q, van den Hengel A, Zhang Y,
MPTV: matching pursuit based total variation minimization for image deconvolution,
TIP, 2019.
|
| 62 |
Liu W, Gong D, Tan M, Shi Q, Yang Y, Hauptmann A,
Learning Distilled Graph for Large-scale Social Network Data Clustering,
TKDE, 2019.
|
| 61 |
Suwanwimolkul S, Zhang L, Gong D, Zhang Z, Chen C, Ranasinghe D, Qinfeng Shi,
An adaptive markov random field for structured compressive sensing,
TIP, 2019.
|
| 60 |
Alireza Abedinvaramin, Hamid Rezatofighi, Damith Ranasinghe, Qinfeng Shi,
SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networks,
IJCAI, 2019.
|
| 59 |
Ehsan Abbasnejad, Qi Wu, Qinfeng Shi, Anton van den Hengel,
What's to know? Uncertainty as a Guide to Asking Goal-oriented Questions,
CVPR, 2019. [pdf]
|
| 58 |
Ehsan Abbasnejad, Qinfeng Shi, Anton van den Hengel, Lingqiao Liu,
A Generative Adversarial Density Estimator,
CVPR (Oral), 2019.
|
| 57 |
Qingsen Yan, Dong Gong, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Ian Reid, Yanning Zhang,
Attention-guided Network for Ghost-free High Dynamic Range Imaging,
CVPR, 2019.
|
| 56 |
Jie Li, You Liu, Dong Gong, Qinfeng Shi, Xia Yuan, Chunxia Zhao, Ian Reid,
Dimensional Decomposition Residual Network for 3D Semantic Scene Completion,
CVPR, 2019.
|
| 55 |
Yuhang Liu, Wenyong Dong, Lei Zhang, Dong Gong, Qinfeng Shi,
Variational Bayesian Dropout,
CVPR, 2019. [pdf]
|
| 54 |
Rui Yao, Guosheng Lin, Qinfeng Shi, Damith Chinthana Ranasinghe,
Efficient dense labelling of human activity sequences from wearables using fully convolutional networks,
Pattern Recognition, 2018.
|
| 53 |
Lei Zhang, Wei Wei, Yanning Zhang, Chunhua Shen, Anton van den Hengel, Qinfeng Shi,
Cluster Sparsity Field: An Internal Hyperspectral Imagery Prior for Reconstruction,
International Journal of Computer Vision, 2018.
|
| 52 |
Yan Yan, Mingkui Tan, Ivor W Tsang, Yi Yang, Qinfeng Shi, Chengqi Zhang,
Fast and Low Memory Cost Matrix Factorization: Algorithm, Analysis and Case Study,
IEEE Transactions on Knowledge and Data Engineering, To Appear, 2018.
|
| 51 |
Suwichaya Suwanwimolkul, Lei Zhang, Dong Gong, Zhen Zhang, Chao Chen, Damith C. Ranasinghe, Qinfeng Shi,
An Adaptive Markov Random Field for Structured Compressive Sensing,
IEEE Transactions on Image Processing, To Appear, 2018.
|
| 50 |
Alireza Abedin Varamin, Ehsan Abbasnejad, Qinfeng Shi, Damith Ranasinghe, Hamid Rezatofighi,
Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables,
MobiQuitous18, 2018.
|
| 49 |
Jie Yang*, Dong Gong*, Lingqiao Liu, Qinfeng Shi,
Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal (* equal contribution),
ECCV18, 2018.
|
| 48 |
Yuhang Liu, Wenyong Dong, Dong Gong, Lei Zhang, Qinfeng Shi,
Deblurring Natural Image Using Super-Gaussian Fields,
ECCV18, 2018.
|
| 47 |
M. Ehsan Abbasnejad, Anthony Dick, Qinfeng Shi, Anton van den Hengel,
Active Learning from Noisy Tagged Images,
BMVC18, 2018.
|
| 46 |
S. Hamid Rezatofighi, Anton Milan, Qinfeng Shi, Anthony Dick, Ian Reid,
Joint Learning of Set Cardinality and State Distribution,
AAAI18, 2018.
|
| 45 |
Dong Gong, Mingkui Tan, Yanning Zhang, Anton Van Den Hengel, Qinfeng Shi,
Self-paced Kernel Estimation for Robust Blind Image Deblurring,
In International Conference on Computer Vision 2017 (ICCV-17), 2017.
|
| 44 |
Zhen Zhang, Julian McAuley, Yong Li, Wei Wei, Yanning Zhang, Qinfeng Shi,
Dynamic Programming Bipartite Belief Propagation For Hyper Graph Matching,
In The 26th International Joint Conference on Artificial Intelligence (IJCAI-17), 2017.
|
| 43 |
Dong Gong, Jie Yang, Lingqiao Liu, Yanning Zhang, Ian Reid, Chunhua Shen, Anton van den Hengel, Qinfeng Shi,
From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur,
CVPR 2017, 2017.
|
| 42 |
Dong Gong, Mingkui Tan, Yanning Zhang, Anton van den Hengel, Qinfeng Shi,
MPGL: An Efficient Matching Pursuit Method for Generalized LASSO,
Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2017, Oral.
|
| 41 |
Zhen Zhang, Qinfeng Shi, Julian McAuley, Wei Wei, Yanning Zhang, Rui Yao, Anton Van Den Hengel,
Solving constrained combinatorial optimisation problems via MAP inference without high-order penalties,
Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2017.
|
| 40 |
Lei Zhang, Wei Wei, Yanning Zhang, Chunhua Shen, Anton van den Hengel, Qinfeng Shi,
Cluster Sparsity Field for Hyperspectral Imagery Denoising,
European Conference on Computer Vision (ECCV 16), 2016.
|
| 39 |
Wei Emma Zhang, Mingkui Tan, Quan Z. Sheng and Qinfeng Shi,
Efficient Orthogonal Non-negative Matrix Factorization over Stiefiel Manifold,
ACM International Conference on Information and Knowledge Management (CIKM 2016), 2016, Oral.
|
| 38 |
Zhen Zhang, Qinfeng Shi, Julian McAuley, Wei Wei, Yanning Zhang, Anton Van Den Hengel,
Pairwise Matching through Max-Weight Bipartite Belief Propagation,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 16), 2016.
|
| 37 |
Seyed Hamid Rezatofighi, Anton Milan, Zhen Zhang, Qinfeng Shi, Anthony Dick, Ian Reid,
Joint Probabilistic Matching Using m-Best Solutions,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 16), 2016, Oral.
|
| 36 |
Dong Gong, Mingkui Tan, Yanning Zhang, Anton Van den Hengel, Qinfeng Shi,
Blind Image Deconvolution by Automatic Gradient Activation,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 16), 2016.
|
| 35 |
Mingkui Tan, Shijie Xiao, Junbin Gao, Dong Xu, Anton Van Den Hengel, Qinfeng Shi,
Proximal Riemannian Pursuit for Large-scale Trace-norm Minimization,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 16), 2016.
|
| 34 |
Mingkui Tan, Yan Yan, Li Wang, Ivor Tsang, Anton van den Hengel and Qinfeng Shi,
Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data,
AAAI16, Phoenix, Arizona USA, February 12-17, 2016.
|
| 33 |
Seyed Hamid Rezatofighi, Anton Milan, Zhen Zhang, Qinfeng Shi, Anthony Dick, Ian Reid,
Joint Probabilistic Data Association Revisited,
International Conference on Computer Vision 2015 (ICCV 15), Santiago, Chile, December 11-18, 2015.
|
| 32 |
Lei Zhang, Wei Wei, Yanning Zhang, Fei Li, Chunhua Shen and Qinfeng Shi,
Hyperspectral Compressive Sensing Using Manifold-Structured Sparsity Prior,
International Conference on Computer Vision 2015 (ICCV 15), Santiago, Chile, December 11-18, 2015.
|
| 31 |
Ming Yin, Junbin Gao, Zhouchen Lin, Qinfeng Shi and Yi Guo,
Dual Graph Regularized Latent Low-rank Representation for Subspace Clustering,
IEEE Transactions on Image Processing, To Appear, 2015.
|
| 30 |
Yan Yan, Mingkui Tan, Ivor W Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi,
Scalable Maximum Margin Matrix Factorization by active Riemannian Subspace Search,
International Joint Conference on Artificial Intelligence (IJCAI 15), Buenos Aires, To Appear, July 25 - 31, 2015, Long Oral.
|
| 29 |
Julian McAuley, Christopher Targett, Qinfeng Shi, Anton van den Hengel,
Image-based recommendations on styles and substitutes,
The 38th Annual ACM SIGIR conference (SIGIR 15), Santiago de Chile, To Appear, August 9-13 2015, Oral.
|
| 28 |
Mingkui Tan, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Junbin Gao, Fuyuan Hu, Zhen Zhang,
Learning Graph Structure for Multi-label Image Classification via Clique Generation,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 15), Boston USA, 7-12 June, 2015.
|
| 27 |
Fumin Shen, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, Zhenmin Tang, Heng Tao Shen,
Hashing on nonlinear manifolds,
IEEE Transactions on Image Processing, To Appear, 2015.
|
| 26 |
Hui Li, Chunhua Shen, Anton van den Hengel, Qinfeng Shi,
Worst-case linear discriminant analysis as scalable semidefinite feasibility problems,
IEEE Transactions on Image Processing, To Appear, 2015.
|
| 25 |
Qinfeng Shi, Mark Reid, Tiberio Caetano, Anton van den Hengel, and Zhenhua Wang,
A Hybrid Loss for Multiclass and Structured Prediction,
IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 37(1): 2-12, 2015. [arXiv: 1402.1921 ]
|
| 24 |
Guosheng Lin, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, David Suter,
Fast Supervised Hashing with Decision Trees for High-Dimensional Data,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 14), June 2014.
|
| 23 |
Sakrapee Paisitkriangkrai, Chunhua Shen, Qinfeng Shi, Anton van den Hengel,
RandomBoost: Simplified Multiclass Boosting Through Randomization,
IEEE Transactions on Neural Networks and Learning Systems, 25(4): 764-779, April. 2014. [ pdf]
|
| 22 |
Zhen Zhang, Qinfeng Shi, Yanning Zhang, Chunhua Shen, and Anton van den Hengel,
Constraint Reduction using Marginal Polytope Diagrams for MAP LP Relaxations,
Tech Report, Dec. 2013. [arXiv:1312.4637]
|
| 21 |
Zhenhua Wang, Qinfeng Shi, Chunhua Shen, Anton van den Hengel,
Bilinear Programming for Human Activity Recognition with Unknown MRF Graphs,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 13), Portland, USA, June 25-27, 2013. [ pdf]
|
| 20 |
Rui Yao, Qinfeng Shi, Chunhua Shen, Yanning Zhang, Anton van den hengel,
Part-based visual tracking with online latent structural learning,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 13), Portland, USA, June 25-27, 2013. [ pdf][ supplementary] [ code ]
|
| 19 |
Fumin Shen, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, Zhenmin Tang,
Inductive hashing on manifolds,
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 13), Portland, USA, June 25-27, 2013.
[ pdf][ supplementary]
|
| 18 |
Rui Yao, Qinfeng Shi, Chunhua Shen, Yanning Zhang, Anton van den hengel,
Robust Tracking with Weighted Online Structured Learning,
The 12th European Conference on Computer Vision (ECCV 12), Firenze, Italy, Oct. 7-13, 2012.
[ pdf] [ supplementary]
|
| 17 |
Qinfeng Shi, Chunhua Shen, Rhys Hill, Anton van den Hengel,
Is margin preserved after random projection?,
The 29th International Conference on Machine Learning (ICML 12), Edinburgh, Scotland, June 26-July 1, 2012. [ pdf][ errata][ code ].
|
| 16 |
Xi Li, Chunhua Shen, Qinfeng Shi, Anthony dick, Anton van den Hengel,
Non-sparse Linear Representations for Visual Tracking with Online Reservoir Metric Learning,
In IEEE Computer
Society Conference on Computer Vision and Pattern Recognition (CVPR 12), 2012. [ link]
|
| 15 |
Qinfeng Shi, Anders Eriksson, Anton van den Hengel, Chunhua Shen,
Is face recognition really a Compressive Sensing problem?
In IEEE Computer
Society Conference on Computer Vision and Pattern Recognition (CVPR 11), Colorado Springs, USA, June 21-23, 2011. [ pdf][ code ]
|
| 14 |
Hanxi Li, Chunhua Shen, Qinfeng Shi,
Real-time visual tracking with compressed sensing,
In IEEE Computer
Society Conference on Computer Vision and Pattern Recognition (CVPR 11), Colorado Springs, USA, June 21-23, 2011.
|
| 13 |
Qinfeng Shi, Li Cheng, Li Wang and Alex Smola,
Discriminative Human Action Segmentation and Recognition using Semi-Markov Model,
International Journal of Computer Vision, In International Journal of Computer Vision, 93(1):22-32, 2011. DOI: 10.1007/s11263-010-0384-0. [pdf]
|
| 12 |
Qinfeng Shi, Mark Reid, Tiberio Caetano, Anton van den Hengel,
A Hybrid Loss for Multiclass and Structured Prediction,
Techinque Report. 2010. [ pdf]
|
| 11 |
Qinfeng Shi, Hanxi Li, Chunhua Shen,
Rapid Face Recognition Using Hashing,
In IEEE Computer
Society Conference on Computer Vision and Pattern Recognition (CVPR 10), San Francisco, USA, June 13-18, 2010. [ pdf][ code ]
|
| 10 |
Qinfeng Shi, Mark Reid, Tiberio Caetano,
Hybrid model of Conditional Random Field and Support Vector Machine,
Workshop at the 23rd Annual Conference on Neural Information Processing Systems, Canada, Dec. 2009. [ pdf]
|
| 9 |
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alex Smola and Vishy Vishwanathan,
Hash Kernels for Structured Data,
Journal of Machine Learning Research, Nov. 2009. [ pdf]
|
| 8 |
Qinfeng Shi, Li Cheng, Luping Zhou and Dale Schuurmans,
Discriminative Maximum Margin Image Object Categorization with Exact Inference,
The 5th International Conference on Image and Graphics, Xi'an, Sep 20-23, 2009. [ pdf]
|
| 7 |
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alex Smola, Alex Strehl and Vishy Vishwanathan,
Hash Kernels,
Twelfth International Conference on
Artificial Intelligence and Statistics, Florida, Apirl 14-19, 2009. [pdf]
|
| 6 |
Qinfeng Shi, Li Wang, Li Cheng and Alex Smola,
Discriminative Human Action Segmentation and Recognition using Semi-Markov Model (short version with cutting plane method),
In IEEE Computer
Society Conference on Computer Vision and Pattern Recognition (CVPR 08),Anchorage, Alaska, June 23-28, 2008. [pdf]
|
| 5 |
Qinfeng Shi, Yasemin Altun , Alex Smola and S.V.N. Vishwanathan,
Automatic Paragraph Segmentation via Max-Margin Semi-Markov Models,
In Proceedings of the 2007 Conference on
Empirical Methods in Natural Language Processing (EMNLP-CoNLL07) , Jun 2007, pp. 640-648. [pdf]
|
| 4 |
Ying Li, Qinfeng Shi, Yanning Zhang and Rongchun Zhao,
A study on Automated segmentation algorithm of SAR Image,
Journal of Electronics & Information Technology (Chinese), 2006.
|
| 3 |
Qinfeng Shi, Yanning Zhang,
Linear Feature Detection based on Beamlet Analysis,
in Proc. of the Third National Conference on Signal and Information Processing (Chinese), 2004, pp. 206-209
|
| 2 |
Qinfeng Shi, Ying Li, Yanning Zhang,
A New Automatic Segmentation for Synthetic Aperture Radar Images,
in Proc. of the International Symposium on Intelligent Multimedia, Video & Speech Processing (ISIMP'04), 2004, pp. 739-742
|
| 1 |
Qinfeng Shi, Yanning Zhang,
Adaptive Linear Feature Detection based on Beamlet,
in Proc. of the Third International Conference on Machine Learning and Cybernetics (ICMLC'04), 2004, pp. 3981-3984.
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