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彭玺

日期:2017-09-08 来源:计算机学院 作者: 浏览:



 

 

 

 

姓名:彭玺

职称:研究员(正高)

职务:无

所在系所:计算机科学

电话:

电子邮箱:pengxi@scu.edu.cn

个人主页:http://www.machineilab.org/users/pengxi/index.html

办公地址:成都市一环路南一段川大望江校区基教B320

研究方向:机器学习、计算机视觉

 

 

个人简介

彭玺,2013年12月毕业于四川大学计算机学院;2014年至2017年,就职于新加坡科技局资讯通信研究院(Institute for Infocomm, A*STAR)担任研究员(Scientist)和项目主管(CO-PI);2017年被四川大学引进任特聘研究员;2018年入选四川省千人计划。主要研究方向包括表示学习、深度神经网络、聚类、可微编程等,并在计算机视觉、视频监控、图像分析和理解等相关领域开展应用基础研究。至2018年,彭玺博士共计在中国计算机学会A类推荐期刊/会议及IEEE Trans等国际重要SCI期刊上发表学术论文30余篇。发表的一作论文中包含多篇ESI热点论文(前1‰)和高被引论文(前1%);是IEEE Access,IEEE Trans Neural Netw Learn Syst和 Image Vis Comput等多个国际重要SCI期刊的副主编/特邀编委,ECCV16专题报告组织主席、AAAI17分会主席、IJCAI17领域主席、VCIP17领域主席,VALSE18注册主席;是视觉与学习青年学者研讨会(VALSE)理事会理事,计算机学会计算机视觉专委会委员,CCF YOCSEF成都分会AC委员。

 

 

项目成果及获奖荣誉

[1] 2018年,入选“四川省千人计划”;

[2] 提出的用于新科技局无人车的“大规模场景感知算法”被选为新加坡科技局突出成果(Highlight in A*STAR Research);

[3] 一作论文获“国际电气和电子工程师协会成都分会优秀学生论文”(IEEE CHENGDU Section Excellent Student Paper)。

 

 

论文著作

1. Hongyuan Zhu, Xi Peng*, Vijay Chandrasekhar, Liyuan Li, Joo-Hwee Lim, DehazeGAN: When Image Dehazing Meets Differential Programming, the 27th International Joint Conference on Artificial Intelligence (IJCAI’18), Stockholm, Sweden, July 13-19, 2018. (Oral)

2. Joey Tianyi Zhou, Kai Di, Jiawei Du, Xi Peng*, et al., SC2Net: Sparse LSTMs for Sparse Coding, the 32th AAAI Conference on Artificial Intelligence (AAAI'18), New Orleans, Louisiana, 2-7 Feb., 2018. (Oral)

3. Xi Peng, Jiashi Feng, Jiwen Lu, Wei-Yun Yau and Zhang YiCascade Subspace Clustering, The 31th AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, Feb. 4-9, 2017.  

4. Xi Peng, Shijie Xiao, Jiashi Feng, Wei-Yun Yau and Zhang Yi, Deep Subspace Clustering with Sparsity Prior, The 25th International Joint Conference on Artificial Intelligence (IJCAI’16), pp: 1925-1931, New York, July 9-15, 2016. Oral

5. Xi Peng, Zhang Yi, and Huajin Tang,  Robust Subspace Clustering via Thresholding Ridge Regression, The 29th AAAI Conference on Artificial Intelligence (AAAI’15), pp 1745-1751, Austin, Texas, USA, January 25-29, 2015.

6. Zhiding Yu, Weiyang Liu, Wenbo Liu, Xi Peng, Zhuo Hui and B.V.K. Vijaya Kumar, Generalized Transitive Distance with Minimum Spanning Random Forest, The 24th International Joint Conference on Artificial Intelligence (IJCAI’15), Buuenos Aires, Argentina, July 25-31, 2015. Oral

7. Xi Peng, Lei Zhang and Zhang Yi, Scalable Sparse Subspace Clustering, The 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), pp 430-437, Portland, Oregon, USA, June, 2013.

8. Joey Tianyi Zhou, Heng Zhao, Xi Peng*, Meng Fang, Zheng Qin and Rick Siow-Mong Goh, Transfer Hashing: From Shallow To Deep, IEEE Trans. on Neural Networks and Learning Systems (TNNLS), April, 2018. DOI: 10.1109/TNNLS.2018.2827036

9. Hongyuan Zhu, Romain Vial, Shijian Lu, Xi Peng*, Huazhu Fu, Yonghong Tian, and Xianbin Cao, YoTube: Searching Action Proposal via Recurrent and Static Regression Networks, IEEE Trans. on Image Processing (TIP), vol. 27, no. 6, pp: 2609-2622, June, 2018. DOI: 10.1109/TIP.2018.2806279.

10. Xinxing Xu, Shijie Xiao, Zhang Yi, Xi Peng*, and Yong Liu, Orthogonal Principal Coefficients Embedding for Unsupervised Subspace Learning, IEEE Trans. On Cognitive and Developmental Systems (TCDS), vol. 10, no. 2, pp:280 - 289, June, 2018DOI:10.1109/TCDS.2017.2686983.

11. Xi Peng, Canyi Lu, Zhang Yi, and Huajin Tang, Connections Between Nuclear Norm and Frobenius Norm Based Representation, IEEE Trans. on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 1, pp. 218-224, Jan. 2018. DOI: 10.1109/TNNLS.2016.2608834. (ESI Hot Paper, 0.1% highly cited)

12. Xi Peng, Jiwen Lu, Zhang Yi, and Yan Rui, Automatic Subspace Learning via Principal Coefficients Embedding, IEEE Trans. on Cybernetics (TCYB), vol. 47, no. 11, pp. 3583-3596, Nov. 2017. DOI:10.1109/TCYB.2016.2572306. (ESI Hot Paper, 0.1% highly cited)

13. Xi Peng, Bo Zhao, Rui Yan, Huajin Tang, and Zhang Yi, Bag of Events: An Efficient and Online Probability-based Low-level Feature Extraction Method for AER Image Sensors, IEEE Trans. on Neural Networks and Learning Systems (TNNLS), vol. 28, no. 4, pp. 791-803, Apr. 2017.  DOI:10.1109/TNNLS.2016.2536741.

14. Xi Peng, Zhiding Yu, Huajin Tang, and Zhang Yi, Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering, IEEE Trans. on Cybernetics (TCYB), vol. 47, no. 4, pp. 1053-1066, Apr. 2017. DOI:10.1109/TCYB.2016.2536752. 

15. Xi Peng, Huajin Tang, Lei Zhang, Zhang Yi, and Shijie Xiao, A Unified Framework for Representation-based Subspace Clustering of Out-of-sample and Large-scale Data, IEEE Trans. on Neural Networks and Learning Systems (TNNLS), vol. 27, no. 12, pp. 2499-2512, Dec. 2016. DOI:10.1109/TNNLS.2015.2490080. (This paper has been selected as highlight in A*STAR Research) 

16. Xi Peng, Miaolong Yuan, Zhiding Yu, Wei-Yun Yau, and Lei Zhang, Semi-supervised Learning with L2graph, Neurocomputing, Volume 208, 5 October 2016, Pages 143-152, DOI: 10.1016/j.neucom.2015.11.112.

17. Xi Peng, Rui Yan, Bo Zhao, Huajin Tang, and Zhang Yi, Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification, Knowledge based Systems, vol:90, 14-22, 2015.

18. Xi Peng, Lei Zhang, Zhang Yi and K. K. Tan, Learning Locality-Constrained Collaborative Representation for Robust Face Recognition, Pattern Recognition 47 (9), 2794-2806, 2014.

19. Xi Peng, Liangli Zhang and Zhang Yi, Inductive Sparse Subspace Clustering, IET Electronics Letters, 49 (19), 1222-1224, 2013.

20. Xi Peng, Zhang Yi, Xiaoyong Wei, Dezhong Peng and Yongsheng Sang, Free-Gram Phrase Identification for Modeling Chinese Text, Information Processing Letters, 113 (4), 137-144, 2013.

 

招生专业与方向

077500 计算机科学与技术

08 (全日制)机器智能与类脑计算

07 (全日制)计算机视觉

 

083500 软件工程

02 (全日制)软件智能

07 (非全日制)计算机视觉与图像处理

 

085211 计算机技术

10 (全日制)机器智能

22 (非全日制)机器智能

16 (非全日制)计算机视觉与图像处理

 

 

 

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