"Make everything as simple as possible, but not simpler."-by Albert Einstein
l 08/2010~ 12/2013 PhD Student, Dept. of Computing, The Hong Kong Polytechnic University, Hong Kong, China.
l 09/2006~07/2009 M.Sc., Dept. of Electronic Engineering and Information Science, University of Science and Technology of China (USTC), Hefei, China.
l 09/2002~07/2006 B.Sc., Dept. of Electronic Engineering, Ocean University of China, Qingdao, China.
l 12/2013~present, Professor in School of Information and Control, Nanjing University of Information Science & Technology
l 08/2009~08/2010, Research Assistant in Dept. of Computing, The Hong Kong Polytechnic University
l Image segmentation by Level set methods;
l Visual tracking by detection
1. K. Zhang, X. Li, H. Song, and Q. Liu., Visual Tracking using Spatio-Temporally Nonlocally Regularized Correlation Filter., Pattern Recognition, 2018.
2. K. Zhang, Q. Liu, J. Yang, and M-H. Yang., Visual tracking via Boolean map representations., Pattern Recognition, vol. 81, pp. 147-160, 2018. (paper),results)
4. K. Zhang, L. Zhang, K. M. Lam, and D. Zhang, A Level Set Approach to Image Segmentation with Intensity Inhomogeneity., IEEE Trans. Cybernetics, vol.46, no.2, pp. 546-557, 2016. (paper, website&source codes)
5. K. Zhang, Q. Liu, H. Song, and X. Li., A Variational Approach to Simultaneous Image Segmentation and Bias Correction., IEEE Trans. Cybernetics, vol.45, no. 5, pp. 1426-1437, 2015. (paper, source codes)
6. K. Zhang, L. Zhang, and M-H. Yang., Fast Compressive Tracking., IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 36, issue. 10, pp. 2002-2015, 2014. (paper, website&source codes).
7. K. Zhang, L. Zhang, M-H. Yang and Q-H. Hu., Robust Object Tracking via Active Feature Selection., IEEE Trans. Circuits and Systems for Video Technology, vol. 23, issue. 11, pp. 1957-1967, 2013. (paper).
8. K. Zhang, L. Zhang, and M-H. Yang, Real-Time Object Tracking via Online Discriminative Feature Selection., IEEE Trans. Image Processing, vol. 22, issue. 12, pp. 4664-4677, 2013. (paper source code).
9. K. Zhang, L. Zhang, H. Song, and D. Zhang., Re-initialization Free Level Set Evolution via Reaction Diffusion., IEEE Trans. Image Processing , vol. 22, no. 1, pp. 258-271, Jan. 2013. (paper, source codes, website).
10.K. Zhang, H. Song., Real-Time Visual Tracking via Online Weighted Multiple Instance Learning., Pattern Recognition, vol. 46, pp. 397~411, 2013. (paper&source).
11.K. Zhang, L. Zhang, H. Song, and W. Zhou., Active Contours with Selective Local or Global Segmentation: A New Formulation and Level Set Method., Image and Vision Computing , vol.28, issue 4, pp. 668-676, April 2010. (paper, source code website) (citations: 365+). The most cited paper award since 2010.
12.K. Zhang, H. Song, and L. Zhang., Active Contours Driven by Local Image Fitting Energy., Pattern recognition, vol.43, issue 4, pp. 1199-1206, April 2010. (paper, source code) (citations: 278+) The most cited paper award since 2010.
13.K. Zhang, S. Xu,W. Zhou, and B. Liu., Active Contours Based On Image Laplacian Fitting Energy., Chinese Journal of Electronics, vol. 18, no. 2, pp. 281-284, 2009. (paper_long, paper_short , source code).
14.H. Song, B. Huang, Q. Liu, and K. Zhang., Improving the spatial resolution of Landsat TM/ETM+ through fusion with SPOT5 images via learning-based super-resolution., IEEE Trans. Geoscience and Remote Sensing, 2014. (paper)
15.H. Song, B. Huang, and K. Zhang., Shadow Detection and Reconstruction in High-Resolution Satellite Images via Morphological Filtering and Example-Based Learning., IEEE Trans. Geoscience and Remote Sensing, 52(5), pp. 2545-2554, 2014. (paper).
16.H. Song, B. Huang, and K. Zhang., A Globally Statistical Active Contour Model for Segmentation of Oil Slick in SAR Imagery., IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, issue 6, pp. 2402-2409, 2013. (paper).
17.H. Song, B. Huang, K. Zhang, and H. Zhang., Spatio-Spectral fusion of Satellite Images based on Dictionary-pair Learning., Information Fusion, vol. 18, pp. 148-160, 2014. (paper).
18.H. Song, G. Wang, K. Zhang., Hypersectral image denoising via low-rank matrix recovery., Remote Sensing Letters, vol. 20, pp. 872-881, 2014.
19. H. Song, G. Wang, K. Zhang., Multiple change detection for multispectral remote sensing images via joint sparse representation., Opt. Eng. 53 (12), 123103
20. F. Li, H. Lu, D. Wang, Y. Wu, and K. Zhang., Dual Group Structured Tracking, IEEE Trans. Circuits and Systems for Video Technology, 2015.
21. J. Yang, K. Zhang, and Q. Liu,. Robust Object Tracking by Online Fisher Discrimination Boosting Feature Selection, Computer Vision and Image Understanding, 2016.
22. W.Chen, K. Zhang, and Q. Liu., Robust visual tracking via patch based kernel correlation filters with adaptive multiple feature ensemble, Neurocomputing, 2016.
23.Q. Liu, J. Yang, K. Zhang, and Y. Wu., Adaptive Compressive Tracking via Online Vector Boosting Feature Selection, IEEE Trans. Cybernetics, 2016.
24.Q. Liu, J. Fan, H. Song, W. Chen, and K. Zhang., Visual Tracking via Nonlocal Similarity Learning, IEEE Trans. Circuits and Systems for Video Technology, 2017.
25.S. Chen, J. Yang, L. Luo, Y. Wei, K. Zhang and Y. Tai., Low-Rank Latent Pattern Approximation With Applications to Robust Image Classification, IEEE Trans. Image Processing, 2017.
26.Q. Liu, J. Yang, J. Deng and K. Zhang., Robust facial landmark tracking via cascade regression, Pattern Recognition, 2017.
27.H. Shuai, Q. Liu, K. Zhang, J. Yang, J. Deng., Cascaded Regional Spatio-Temporal Feature-Routing Networks for Video Object Detection, IEEE Access, 2017.
28.H. Song, Y. Zheng and K. Zhang., Efficient algorithm for piecewise-smooth model with approximately explicit solutions, Electronics Letters, 2017.
29.Z. Li, J. Zhang, K. Zhang and Z. Li., Visual Tracking with Weighted Adaptive Local Sparse Appearance Model via Spatio-Temporal Context Learning, IEEE Trans. Image Processing, 2018.
1. K. Zhang, L. Zhang, Q. Liu, Q. Liu, D. Zhang, and M-H. Yang., Fast Visual Tracking via Dense Spatio-Temporal Context Learning, in Proc. 13th European Conference on Computer Vision (ECCV), Part V, LNCS 8693, pp. 127-141, 2014 (paper, website&source codes, 中文博客).
2. K. Zhang, L. Zhang, M-H.Yang., Real-Time Compressive Tracking, in Proc. 12th European Conference on Computer Vision (ECCV), Part III, LNCS 7574, pp. 864-877, 2012. (paper, source code and website, 中文博客) (citations: 668+) (The most cited paper in ECCV2012 by Google scholar)
3. K. Zhang, L. Zhang, S. Zhang., A Variational Multiphase Level Set Approach to Simultaneous Segmentation and Bias Correction, ICIP 2010 (oral). (paper, source code) (citations: 33+)
4. H. Song, L. Zhang, P. Wang, K. Zhang and X. Li., An Adaptive L1-L2 Hybrid Error Model to Super-resolution, ICIP 2010.
5. J. Yang. J. Deng, K. Zhang, and Q. Liu., Facial Shape Tracking via Spatio-Temporal Cascade Shape Regression, The IEEE International Conference on Computer Vision (ICCV) Workshops, 2015, pp. 41-49.
IEEE Trans. Pattern Analysis and Machine Intelligence, IEEE Trans. Circuits and Systems for Video Technology, IEEE Trans. Neural Networks and Learning Systems, IEEE Trans. Visualization and Computer Graphics, IEEE Trans. Image Processing, IEEE Trans. SMC-C, IEEE Trans. SMC-B, IEEE Signal Processing Letters, IEEE Communication Letters, Pattern Recognition, Signal Processing, EURASIP Journal on Advances in Signal Processing, Biomedical Engineering Online, The Visual Computer, Image and Vision Computing, Neurocomputing, Journal of Biomedical and Health Informatics, Computers&Graphics, Frontiers of Computer Science, SPIE Journal of Electronic Imaging, Signal Processing: Image Communication, Journal of Visual Communication and Image Representation
l Here are the MATLAB codes I have implemented for MILTrack
Last update: May.20,2018