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庞彦伟

Date:2020年08月01日

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:天津大学电气与自动化工程学院26教学楼D424

电子信箱: pyw(at)tju.edu.cn

电话/传真:022-27407780


主要经历:

2004年博士毕业于中国科学技术大学信息与通信工程专业,

20041-200411月微软亚洲研究院媒体计算组访问学生,

2006年于中国科学技术大学电子科学与技术专业博士后流动站出站。

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,

2019年创建天津市类脑智能技术重点实验室并担任实验室主任。


研究方向:

研究领域是深度学习、图像目标检测、图像语义分割、医学图像重建、雷达感知、多传感器协同感知等。主要应用领域是智能驾驶、智能视频监控、智能医学成像设备、智能可穿戴健康设备、智能机器人等。


学术荣誉:

2010年入选教育部新世纪优秀人才支持计划,

2012年承担国家优秀青年科学基金项目(优青)

2013年入选国家万人计划青年拔尖人才支持计划,

2015年入选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。

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, 2018年度中国电子学会自然科学一等奖。

2014年至2019年连续入选Elsevier中国高被引学者名单。是IEEE高级会员。


学术兼职:

IEEE Transactions on Neural Networks and Learning Systems(影响因子8.793),编委

Neural Networks (Elsevier) (影响因子5.535),编委

Pattern Recognition Letters (Elsevier)(影响因子3.255),客座编辑

SCIENCE CHINA Information Sciences (影响因子3.304),青年编委


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,横向项目主要来自清华大学、安徽华米科技信息有限公司、中国汽车技术研究中心、中船重工集团707研究所等国家重点企事业单位和领域内全球领先的企业。


合作交流

清华大学自动化系、软件学院

中科院自动化所模式识别国家重点实验室

英国华威大学、亚伯大学

阿联酋起源人工智能研究院、阿联酋人工智能大学


主要讲授课程:

数字图像处理、模式识别(本科生)

统计模式识别(硕士生)

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)

招生名额:每年招收博士生12名、硕士生4名左右。


论文发表: 

发表学术论文150篇,其中IEEE汇刊论文40篇,包含计算机视觉三大会议CVPR/ICCV/ECCV在内的顶级会议论文30篇。近年部分论文如下:

Y. Pang*, J. Cao, Y. Li, J. Xie, H. Sun, and J. Gong, “TJU-DHD: A Diverse High-Resolution Dataset for Object Detection,” IEEE Transactions on Image Processing, Status: Minor Revision, 2020.

J. Cao, Y. Pang*, S. Zhao*, and X. Li, “High-Level Semantic Networks for Multi-Scale Object Detection,” IEEE Transactions on Circuits Systems for Video Technology, DOI:10.1109/TCSVT.2019.2950526, 2019.

Y. Li, Y. Pang*, J. Cao, J. Shen, and L. Shao, “Improving Single Shot Object Detection with Feature Scale Unmixing,” IEEE Transactions on Image Processing, Status: Major Revision, 2020.

J. Xie, Y. Pang*, M. Khan, R. Anwer, F. Khan, and L. Shao, “Mask-Guided Attention Network and Occlusion-Sensitive Hard Example Mining for Occluded Pedestrian Detection,” IEEE Transactions on Image Processing, Status: Major Revision, 2020.

J. Nie, Y. Pang*, S. Zhao*, J. Han, and X. Li, “Efficient Selective Context Network for Accurate Object Detection,” IEEE Transactions on Circuits and Systems for Video Technology, Status: Major Revision, 2019.

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. Nie, J. Xie, J. Han, and X. Li, “BidNet: Binocular Image Dehazing without Explicit Disparity Estimation,” in Proc. IEEE International Conference on Computer Vision and Pattern Recognition, 2020.

Y. Li, Y. Pang*, J. Shen, J. Cao, and L. Shao, “NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection,” in Proc. IEEE International Conference on Computer Vision and Pattern Recognition, 2020.

W. Wang, H. Zhu, J. Dai, Y. Pang*, J. Shen, and L. Shao “Hierarchical Human Parsing with Typed Part-Relation Reasoning,” in Proc. IEEE International Conference on Computer Vision and Pattern Recognition, 2020.

Z. Ji, X. Liu, Y. Pang*, and X. Li, “SGAP-Net: Semantic-Guided Attentive Prototypes Network for Few-Shot Human-Object Interaction Recognition”, in Proc. AAAI Conference on Artificial Intelligence, 2020.

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, vol. 14, no. 12, pp. 3322-3331, 2019.

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, vol. 30, no. 9, pp. 2779-2793, 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.