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庞彦伟

发布时间: 2018-11-24     来源:

个人资料:

姓名:庞彦伟

职称:教授/博士生导师

学科专业:信息与通信工程(一级学科) 信号与信息处理(二级学科)

通讯地址:天津大学电气自动化与信息工程学院26教学楼D424

电子信箱: pyw@tju.edu.cn

电话/传真:022-27407780

 

总体情况:

庞彦伟,男,1976年生。2004年博士毕业于中国科学技术大学信息与通信工程专业,现为天津大学电气自动化与信息工程学院电子信息工程系教授、博导,天津大学类脑感知与学习实验室主任。研究领域是类脑智能、深度学习、图像识别、图像理解、视觉感知、雷达感知、多传感器协同感知等。主要应用领域是无人驾驶汽车、无人艇、辅助驾驶、智能视频监控、智能人机交互、智能机器人、生物特征识别(身份认证)等。2010年入选教育部新世纪优秀人才支持计划,2012年获得首批国家优秀青年科学基金(优青)2013年入选首批国家万人计划青年拔尖人才支持计划,2015年入选首批教育部青年长江学者,2018年入选科技部中青年科技创新领军人才、天津市131创新型人才团队(天津大学智能驾驶视觉环境感知团队)负责人。获2017年度天津市自然科学三等奖,2017年度辽宁省科技进步二等奖,2017年世界智能大会世界智能驾驶挑战赛领先奖,2018年度中国电子学会自然科学一等奖。自2014年至2018年连续入选Elsevier中国高被引学者名单。是IEEE高级会员。为五个SCI国际期刊的编委或客座编辑。发表学术论文125篇,其中IEEE汇刊论文35篇。

 

科研项目情况:

承担了大量基础研究、应用基础研究等科研项目,科研经费充足,为培养学生的创新能力、实践能力提供了优越的条件。承担的国家级项目主要是国家自然科学基金重点项目、国家重点基础研究发展计划子课题、国家科技创新2030”重大项目子课题、国家自然科学基金面上项目,国际合作项目主要来自诺基亚集团(芬兰)、微软中国等世界一流创新型企业,横向项目主要来自中国汽车技术研究中心、清华大学、中船重工集团707研究所、中国航天科工集团第二研究院、安徽华米科技信息有限公司等国家重点企事业单位和领域内全球领先的企业。

部分代表性科研项目有:

2017.01-2021.12, 国家自然科学基金重点项目,面向无人驾驶汽车的恶劣天气环境下视觉计算技术,负责人;

2019.08-2022.08, 国家科技创新2030-“新一代人工智能重大项目,无人系统自主智能精准感知与操控项目课题感知对象快速精准分割、检测及其跟踪-识别一体化学习,子课题负责人;

2014.08-2019.08, 国家重点基础研究发展计划,网络大数据感知融合与表示方法研究,子课题负责人。

 

主要讲授课程:

(1)     数字图像处理、模式识别(本科生)

(2)     统计模式识别(硕士生)

(3)     统计学习理论及应用(博士生)

 

研究生招生与培养:

专业:信息与通信工程(含信号与信息处理、通信与信息系统)(学术型硕士)、电子与通信工程(专业型硕士)

常规招生名额:每年招收博士生12名、硕士生4名左右。

导师团招生名额:天津大学类脑智能实验室有天津大学研究生招生宣传导师团专项名额(博士生1名、硕士生2),简介见:天大研招办网址http://yzb.tju.edu.cn/xwzx/zxxx/201906/t20190606_313795.htm,硕士推免系统http://202.113.8.92/gstms,博士招生管理系统http://202.113.5.137/bszs/front。推免硕士的,文件要求本科毕业学校一流大学建设高校或所学专业所类属的学科在最新一轮全国高校学科评估结果中列A-档及以上的其他重点高校;申请博士的,文件要求本科毕业学校为双一流建设高校或所学专业所类属的学科在最新一轮全国高校学科评估结果中列B+档及以上的重点高校,硕士毕业学校(不含天津大学)为双一流建设高校或相关领域中科院院所或所学专业所类属的学科在最新一轮全国高校学科评估结果中列B+档及以上的其他重点高校。

论文(部分)

 

Y. Pang*, Y. Li, J. Shen, and L. Shao, “Towards Bridging Semantic Gap to Improve Semantic Segmentation,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

Y. Pang*, J. Xie, M. H. Khan, R. M. Anwer, F. S. Khan, and L. Shao, “Learning to Mask Visible Regions for Occluded Pedestrian Detection,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

J. Cao, Y. Pang*, J. Han, and X. Li , “Hierarchical Shot Detector,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

T. Wang, R. M. Anwer, H. Cholakkal, F. S. Khan, Y. Pang*, Ling Shao, “Learning Rich Features at High-Speed for Single-Shot Object Detection,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

Z. Ji, H. Wang, J. Han*, and Y. Pang*, “Saliency-Guided Attention Network for Image-Sentence Matching,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

J. Nie, R. M. Anwer, H. Cholakkal, F. S. Khan, Y. Pang*, and L. Shao, “Boosted Feature Guided Refinement Network for Single-Shot Detection,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

 

W. Wang, Z. Zhang, S. Qi, J. Shen, Y. Pang, Ling Shao, “Learning Compositional Neural Information Fusion for Human Parsing,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

T. Wang, R. M. Anwer, M. H. Khan, F. S. Khan, Y. Pang, and L. Shao, and J. Laaksonen, “Deep Contextual Attention for Human-Object Interaction Detection,” in Proc. IEEE International Conference on Computer Vision, 2019.

 

A. Yang , H. Wang , Z. Ji, Y. Pang, and L. Shao, ``Dual-Path in Dual-Path Network for Single Image Dehazing,'' International Joint Conferences on Artificial Intelligence (IJCAI), 2019.

 

Y. Wu, Y. Pang*, B. Gao, J. Han, ``Complementary features with reasonable receptive field for road scene 3d object detection,'' in Proc. IEEE International Conference on Image Processing (ICIP), 2019

 

Y. Pang, J. Cao, J. Han*, and J. Wang, "JCS-Net: Joint Classification and Super-resolution for Small-scale pedestrain Detection in Surveillance Images," IEEE Transactions on Information Forensics and Security, 2019 (Accepted)

 

Y. Pang*, T. Wang, R. M. Anwer, F. S. Khan, and L. Shao, "Efficient Featurized Image Pyramid Network for Single Shot Detector," in Proc. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

 

J. Cao, Y. Pang*, X. Li, "Triply Supervised Decoder Networks for Joint Detection and Segmentation," in Proc. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

 

Y. Yu, Z. Ji, Y. Fu, J. Guo, Y. Pang, and Z. Zhang, "Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning," in Proc. Thirty-second Conference on Neural Information Processing Systems (NeuraIPS), 2018

 

Z. Ji, K. Xiong, Y. Pang*, X. Li, "Video Summarization with Attention-Based Encoder-Decoder Networks," IEEE Transactions on Circuits and Systems for Video Technology, 2019.

 

Y. Pang, B. Zhou, and F. Nie*, "Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction," IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2018.2886317, Jan. 10, 2019.

 

Y. Pang, J. Xie, and X. Li*, "Visual Haze Removal by a Unified Generative Adversarial Network," IEEE Transactions on Circuits and Systems for Video Technology, DOI: 10.1109/TCSVT.2018.2880223, Nov. 9, 2018.

 

Y. Pang, J. Xie, F. Nie, and X. Li, “Spectral Clustering by Joint Spectral Embedding and Spectral Rotation,” IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2018.2868742, Oct. 3, 2018.

 

Y. Yu, Z. Ji, J. Guo, and Y. Pang, “Transductive Zero-Shot Learning With Adaptive Structural Embedding ,” IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 4116-4127, 2018.

 

X. Jiang, Y. Pang*, M. Sun, and X. Li, "Cascaded Subpatch Networks for Effective CNNs," IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 7, pp. 2684-2694, 2018.

 

Y. Pang, M. Sun, X Jiang, and X. Li, "Convolution in Convolution for Network in Network," IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 5, pp. 1587-1597, 2018.

 

H. Sun and Y. Pang, "GlanceNets – Efficient Convolutional Neural Networks with Adaptive Hard Example Mining," SCIENCE CHINA Information Sciences, vol. 61, no. 10, pp.109-101, 2018.

 

J. Cao, Y. Pang, and X. Li, "Learning Multilayer Channel Features for Pedestrian Detection,'' IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3210-3220, 2017.

 

Y. Pang, J. Cao, and X. Li, "Learning Sampling Distributions for Efficient Object Detection," IEEE Transactions on Cybernetics, vol. 47, no. 1, pp. 117-129, 2017.

 

Y. Pang, L. Ye, X. Li, and J. Pan, "Incremental Learning With Saliency Map for Moving Object Detection,'' IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 3, pp. 640-651, 2018.

 

J. Cao, Y. Pang, and X. Li, "Pedestrian Detection Inspired by Appearance Constancy and Shape Symmetry," IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5538-5551, 2016. [An extension version of the corresponding CVPR2016 paper]

 

J. Cao, Y. Pang, X. Li, "Pedestrian Detection Inspired by Appearance Constancy and Shape Symmetry," in Proc. International Conference on Computer Vision and Pattern Recognition, 2016.

 

Y. Pang, J. Cao, X. Li, "Cascade Learning by Optimally Partitioning,"IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4148-4161, 2017.

 

Y. Pang, H. Zhu, X. Li, and X. Li, "Classifying Discriminative Features for Blur Detection," IEEE Transactions on Cybernetics, vol. 46, no. 10, pp. 2220-2227, 2016.

 

Y. Pang, H. Zhu, X. Li, and J. Pan, ''Motion Blur Detection with an Indicator Function for Surveillance Machines,'' IEEE Transactions on Industrial Electronics, vol. 63, no. 9, pp. 5592-5601, 2016.

 

C. Li, J. Guo, R. Cong, Y. Pang, B. Wang, ``Underwater Image Enhancement by Dehazing with Minimum Information Loss and Histogram Distribution Prior,'' IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5664-5677, 2016.

 

C. Li, J. Guo, F. Porikli, Y. Pang, "LightenNet: a Convolutional Neural Network for Weakly Illuminated Image Enhancement," Pattern Recognition Letters, vol. 104, pp. 15-22, March 2018.

 

 Z. Ji, Y. Ma, Y. Pang*, X. Li, "Query-Aware Sparse Coding for Web Multi-Video Summarization," Information Sciences, vol. 478, pp. 152-166, 2018.

 

X. Jiang, Y. Pang*, X. Li, J. Pan, and Y. Xie, "Deep Neural Networks with Elastic Rectified Linear Units for Object Recognition," Neurocomputing, vol. 275, pp. 1132-1139, 2018.

 

J. Cao, Y. Pang*, X. Li, and J. Liang, "Randomly Translational Activation Inspired by the Input Distributions of ReLU," Neurocomputing, vol. 275, pp. 859-868, 2018.

 

Z. Ji, W. Zheng, and Y. Pang, "Deep Pedestrain Attribute Recognition Based on LSTM," in Proc. IEEE International Conference on Image Processing, 2017.

 

Z. Ji, Y. Pang*, and X. Li, "Relevance Preserving Projection and Ranking Based on One-Class Classification for Web Image Search Reranking," IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 4137-4147, 2015.

 

Y. Pang, Z. Song, and X. Li, "Truncation Error Analysis on Reconstruction of Signal from Unsymmetrical Local Average Sampling," IEEE Transactions on Cybernetics, vol. 45, no. 10, pp. 2100-2104, 2015.

 

Y. Pang, K. Zhang, Y. Yuan, and K. Wang, “Distributed Object Detection With Linear SVMs,” IEEE Transactions on Cybernetics, vol. 44, no. 11, pp. 2122-2133, 2014.

 

Y. Pang, S. Wang, and Y. Yuan, “Learning Regularized LDA by Clustering,” IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 12, pp. 2191-2201, 2014.

 

Y. Pang, Z. Ji, P. Jing, and X. Li, “Ranking Graph Embedding for Learning to Rerank,” IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 8, pp. 1292-1303, 2013.

 

Q. Hao, R. Cai, Z. Li, L. Zhang, Y. Pang, F. Wu, Y. Rui, “Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition,” in: Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013, pp.  899-906.

 

Z. Song, B. Liu, Y. Pang*, et al., "An Improved Nyquist-Shannon Irregular Sampling Theorem from Local Averages," IEEE Transactions on Information Theory, vol. 58, no. 9, pp. 6093-6100, 2012.

 

Q. Hao, R. Cai, Z. Li, L. Zhang, Y. Pang, and F. Wu, "3D Visual Phrases for Landmark Recognition," in: Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.

 

Y. Pang, Q. Hao, Y. Yuan, T. Hu, R. Cai, L. Zhang, "Summarizing Tourist Destinations by Mining User-Generated Travelogues and Photos, " Computer Vision and Image Understanding (Elsevier), vol. 115, no. 3, pp. 352-363, 2011.

 

Y. Pang, Y. Yuan, X. Li, and J. Pan, "Efficient HOG Human Detection," Signal Processing (Elsevier), vol. 91, no. 4, 773-781, April 2011.

 

Y. Pang, W. Li, Y. Yuan, and J. Pan, “Fully Affine Invariant SURF for Image Matching,” Neurocomputing, vol. 85, pp. 6-10, 2012.

 

Q. Hao, R. Cai, Y. Pang, and L. Zhang. "From One Tree to a forest: a Unified Solution for Structured Web Data Extraction". in Proc. of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Beijing, China. July 24-28, 2011.

 

Y. Pang, X. Li, Y. Yuan, "Robust Tensor Analysis with L1-Norm," IEEE Transactions on Circuits and Systems for Video Technology, vol. 20, no. 2, pp. 172-178, 2010.

 

X. Li and Y. Pang, "Deterministic Column-Based Matrix Decomposition," IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 1, pp. 145-149, 2010.

 

X. Li, Y. Pang, and Y. Yuan, "L1-norm-based 2DPCA," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 40, no. 4, pp. 1170-1175, August 2010.

 

Y. Yuan, Y. Pang, X. Li, "Footwear for Gender Recognition," IEEE Transactions on Circuits and Systems for Video Technology, vol. 20, no. 1, pp. 131-135, 2010.

 

X. Lu, C. Wang, J. Yang, Y. Pang and L. Zhang, "Photo2Trip: Generating Travel Routes From Geo-tagged Photos for Trip Planning," in Proc. ACM Multimedia, 2010.

 

Q. Hao, R. Cai, C. Wang, R. Xiao, J. Yang, Y. Pang, L. Zhang, “Equip Tourists With Knowledge Mined from Travelogues,” in Proc. World Wide Web Conference (WWW), 2010, pp. 401-410.

 

Y. Pang, Y. Yuan, and X. Li, "Iterative Subspace Analysis Based on Feature Line Distance," IEEE Transactions on Image Processing, vol. 18, no. 4, pp. 903-907, 2009.

 

Y. Pang, X. Li, Y. Yuan, D. Tao, J. Pan, “Fast haar transform based Feature Extraction for Face Representation and Recognition,” IEEE Transactions on Information Forensics and Security , vol. 4, no. 3, pp. 441-450, 2009.

 

Y. Yuan, X. Li, Y. Pang, X. Lu, D. Tao, "Binary Sparse Nonnegative Matrix Factorization," IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 5, pp. 772-777, 2009.

 

Q. Hao, R. Cai, X. Wang, Y. Pang, and L. Zhang, "Generating Location Overviews with Images and Tags by Mining User-Generated Travelogues," in Proc. ACM Multimedia, 2009.

 

Y. Pang, Y. Yuan, X. Li, "Gabor-based Region Covariance Matrices for Face Recognition," IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no. 7, pp. 989-993, 2008.

 

Y. Pang, D. Tao, Y. Yuan, X. Li, "Binary Two-Dimensional PCA," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 38, no. 4, pp. 1176-1180, 2008.

Y. Pang, Y. Yuan, X. Li, "Effective Feature Extraction in High-Dimensional Space," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics , vol. 38, no. 6, pp. 1652-1656, 2008.

 

Y. Pang, Y. Yuan, and X. Li, "Generalised Nearest Feature Line for Subspace Learning," Electronics Letters, vol. 43, no. 20, pp. 1079-1080, 2007.

 

Y. Pang, Z. Liu, and N. Yu, "Kernel Neighborhood Preserving Projections for Face Recognition," Acta Electronic Sinica, vol. 34, no. 8, pp. 1542-1544, 2006.

 

Y. Pang, L. Zhang, Z. Liu, N. Yu, and H. Li, "Neighborhood Preserving Projections (NPP): A Novel Linear Dimension Reduction Method," Lecture Notes in Computer Science, vol. 3644, pp. 117-125, 2005.

 

Y. Pang, H. Li, R. Zhang, and Z. Liu, "Face Recognition Using Neighborhood Preserving Projections," Lecture Notes in Computer Science, vol. 3768, pp. 854-864

 

 

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