General

Qixiang Ye received his B.S. and M.S. degrees in mechanical & electrical engineering from Harbin Institute of Technology (HIT) in 1999 and 2001 respectively, and a Ph.D. degree from the Institute of Computing Technology, Chinese Academy of Sciences in 2006. Since 2016 he has been a full professor at the University of the Chinese Academy of Sciences. He was a visiting assistant professor of University of Maryland Institute of Advanced Computer Studies (UMIACS) until Jan. 2014, and a visiting scholar at Duke University at 2016. His research interests include visual object sensing and machine learning, particularly for weakly supervised and self-supervised visual modeling. He was a recipient of the Sony Outstanding Paper Award and the LuJiaXi Young Researcher Award. He is a Senior Member of IEEE and on the editorial board of Journal of Visual Computer (Springer).


Homepage: www.ucassdl.cn
Email: qxye at ucas dot ac dot cn
Google : ScholarPage
Address: School of Electronics, Electrical and Communication Engineering,
University of Chinese Academy of Sciences, A-2 BLDG, RM.457, 
Huaibei Zhuang, Huairou District, Beijing, China, 101408.

Education

Bachelor of science, Harbin Institute of Technology, China, July 1999
Master of science, Harbin Institute of Technology, China. July 2001
Ph.D in computer science, Institute of Computing Technology, Chinese Academy of Sciences, April 2006

Experience

Assistant Professor of University of Chinese Academy of Sciences, from April 2006 
Associate Professor of University of Chinese Academy of Sciences, from July 2009 
Visiting Assitant Professor of University of Maryland, College Park, from 2012 to 2013

Visiting Scholar of Electrical and Computer Engineering, Duke, 2016 

Professor of University of Chinese Academy of Sciences, from January 2016 

Students

   
PH.D and Masters

1. Fang Wan            Ph. D student from fall 2016. Research Interests: Weakly Supervised Object Detection

2. Tianliang Zhang  Ph. D student from fall 2017. Research Interests: Visual Object Detection

3. Chang Liu             Ph. D student from fall 2017. Research Interests: Deep Learning Modeling

4. Boyu Yang            Ph. D student from fall 2018. Research Interests: Robot Learning 

5. Caijing Miao         Master student from fall 2016. Research Interests:  Weakly Supervised Object Discovery

6. Haolan Xue           Master student from fall 2017. Research Interests:  Visual Object Detection

7. Wei Gao                Master student from fall 2018. Research Interests:  Transferring Learnng and Self-learning

8. Xiaosong Zhang   Master student from fall 2018. Research Interests:  Visual Object Detection

Album

1. Bo Wu                  (2011)  Master ,   Agricalture Bank of China

2. Dongsheng Yu     (2011)   Master,   Tecent

3. Jixiang Liang        (2013)  Master,    Agricalture Bank of China  (Hornored Natinal Scholarship 2012) 

4. Yaozhang             (2015)  Master,    China Aerospace Science and Industrial Corporation

5. Yanting Cui           (2015)  Master,   Alibaba

6. Xiansong Huang   (2017)  Master,   Ctrip

7. Yanran  Liu            (2017)  Master,   Datang Telecom

8. Wei Ke                   (2018)  Ph. D ,   Carnegie Mellon University,  (Hornored Natinal Scholarship, CAS President Scholarship 2017) 

Honors & Distinctions

1.Outstanding Researcher of Youth Innovation Promotion Association, Chinese Academy of Sciences, 2018. 

2."LuJiaXi" Outstanding Young Researcher Awards, 2014
3.Top-10 most Cited Papers in The Past Five Years of Image and Vision Computing, 2010
4.Outstanding Course of Chinese Academy of Sciences, 2007 and 2009
5.CAS-Sony Outstanding Paper Award 2005
6.Scholarship of Institute of Computing Technology, Chinese Academy of Sciences, 2005

Publications & Code

Selected Conference Papers:

[1] C. Liu, W. Ke, F. Qin, Q. Ye, "Linear Span Network for Object Skeleton Detection," to appear in European Computer Vision Conference (ECCV), 2018. [pdf]-[source code]

[2] F. Wan, P. Wei, Z. Han, J. Jiao, Q. Ye, “Min-entropy Latent Model for Weakly Supervised object Detection,”   in Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2018: 1297-1306. [pdf]-[source code]

[3] Y. Zhou, Y. Zhu, Q. Ye, Q. Qiu, J. Jiao, “Weakly Supervised Instance Segmentation using Class Peak Response,”   in Proc. of  IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2018 (Spotlight). [pdf]-[source code]

[4] W. Deng, L. Zheng, Q. Ye, J. Jiao, “Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification,”  in Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2018.  [pdf]-[source code]

[5] Q. Ye, Z. Zhang, Q. Qiu, B. Zhang, J. Chen, and G. Sapiro, "Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model," in Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2017. [pdf]-[source code]-[bibtex]

[6] W. Ke, J. Chen, J. Jiao, and Q. Ye, "SRN: Side-output Residual Network for Object Symmetry Detection in the Wild," in Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2017: 302-310. (Oral). [pdf]-[source code]-[bibtex]

[7] Y. Zhou, Q. Ye, Q. Qiu, and J. Jiao, "Oriented Response Networks," in Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2017. [pdf]-[source code]-[bibtex]

[8] Y. Zhu, Y. Zhou, Q. Ye, Q. Qiu, and J. Jiao, "Soft Proposal Network for Weakly Supervised Object Localization," in Proc. of IEEE Int. Conf. on Computer Vision (ICCV), 2017. [pdf]-[source code]-[bibtex]

[9] R. Xu, B. Zhang, Q. Ye, J. Jiao, "Cascaded L1-norm Minimization Learning (CLML) Classifier for Human Detection," in Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2010. [pdf]-[bibtex]


Selected Journal Papers

[10] Z. Han, P. Wang, Q. Ye, "Adaptive Discriminative Deep Correlation Filter for Visual Object Tracking," IEEE Transactions on Circuit and System on Video Technology, 2019 (To Appear).

[11] P. Wei, F. Qin, F. Wan, Y. Zhu, J. Jiao and Q. Ye, "Correlated Topic Vector for Scene Classification", IEEE Transactions on Image Processing, 26(7):3221-3234 (2017). [pdf]-[bibtex]

[12] S. Gao, Q. Ye, J. Xing, A. kuijper, Z. Han, J. Jiao, X. Ji, "Beyond Group: Multiple Person Tracking via Minimal Topology-Energy-Variation," IEEE Transactions on Image Processing, 26(12):5575-5589 (2017)[pdf]-[bibtex]

[13] B. Zhang, Z. Li, X. Cao, Q. Ye, C. Chen, L. Shen, A. Perina, and R. Ji,"Output Constraint Transfer for Kernelized Correlation Filter in Tracking," IEEE Transactions on Systems, Man, and Cybernetics, 47(4):693-703 (2017).  [pdf]-[bibtex]

[14] Q. Ye, D. S. Doermann, "Text Detection and Recognition in Imagery: A Survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(3):1480-1500 (2015). [pdf]-[bibtex]

[15] S. Gao, Z. Han, C. Li, Q. Ye, J. Jiao, "Real-time Multi-pedestrian Tracking in Traffic Scenes via an RGB-D based Layered Graph Model," IEEE Transactions on Intelligent Transportation Systems, 16(5): 2814-2825 (2015). [pdf]-[bibtex]

[16] L. Zhang, Q. Ye, W. Yang, J. Jiao, "Weld Line Detection and Tracking via Spatial-Temporal Cascaded Hidden Markov Models and Cross Structured Light," IEEE Transactions on Instrumentation and Measurement, 6(4):742-752 (2014). [pdf]-[bibtex]

[17] Q. Ye, Z. Han, J. Jiao, J. Liu, "Human Detection in Images via Piecewise Linear Support Vector Machines," IEEE Transactions on Image Processing, 22(2):778-789 (2013). [pdf]- [source code]-[bibtex]

[18] Q. Ye, J. Liang, J. Jiao, "Pedestrian Detection in Video Images via Error Correcting Output Code Classification of Manifold Subclasses," IEEE Transactions on Intelligent Transportation Systems, 13(1): 193-202 (2012). [pdf]-[bibtex]

[19] R. Xu, J. Jiao, B. Zhang, Q. Ye, "Pedestrian Detection in Images via Cascaded L1-norm Minimization Learning Method," Pattern Recognition, 45(7):2573-2583 (2012). [pdf]-[bibtex]

[20] Z. Han, J. Jiao, Q. Ye, J. Liu, "Visual Object Tracking Via Sample-Based Adaptive Sparse Representation, " Pattern Recognition, 44(9): 2170-2183 (2011). [pdf]-[bibtex]