冯松鹤

博士、教授、博士生导师

基本信息

办公电话:N/A 电子邮件: shfeng@bjtu.edu.cn
通讯地址:北京交通大学计算机学院9教北524 邮编:100044

个人简介

       北京交通大学计算机与信息技术学院教授,博士生导师,入选首批北京交通大学青年英才培育计划(2015-2017),获得2023年度北京图象图形学学会优秀导师提名奖。主要研究领域为弱监督机器学习算法及其在图像语义理解中的应用。累计主持国家自然科学基金面上及青年项目3项,北京市自然科学基金面上项目3项,教育部博士点基金1项,中国博士后科学基金特别资助项目及面上项目各1项。在包括 IEEE TPAMI, IEEE TIP, IEEE TKDE, ACM TKDD, IEEE TMM, IEEE TCSVT, IEEE TCYB, ACM TIST 等知名学术期刊以及 ICCV, AAAI, IJCAI, ACM SIGKDD, ACM Multimedia 等知名国际会议上累计发表各类研究论文近百篇。

教育背景

  • 2003.09 - 2009.01  北京交通大学,计算机应用技术,直博,博士 (导师:须 德 教授);
  • 1999.09 - 2003.07  北京交通大学,计算机科学与技术,学士;

工作经历

  • 2017.12 - 至今         北京交通大学,计算机与信息技术学院,教授;
  • 2024.01 - 2024.02   康考迪亚大学(加拿大),高级研究学者;
  • 2017.09 - 2017.12   德累斯顿工业大学(德国),访问学者;
  • 2013.10 - 2014.10   密歇根州立大学(美国),访问学者 (合作导师:Rong Jin)
  • 2012.12 - 2017.11   北京交通大学,计算机与信息技术学院,副教授;
  • 2011.01 - 2012.11   北京交通大学,计算机与信息技术学院,讲师; 
  • 2009.04 - 2010.12   北京交通大学,计算机与信息技术学院,师资博士后

研究方向

  • 理论层面:聚焦于弱监督机器学习算法研究,包括但不限于:Multi-View Clustering、Multi-View Multi-Label Learning、Partial-Label Learning、Partial Multi-Label Learning等;
  • 应用层面:聚焦于深度学习框架下的图像语义理解算法研究,包括但不限于:Multi-Label Image Classification、Generalized (Multi-Label) Zero-Shot Learning、Novel Category Discovery、Domain Adaptation/Generalization等;

研究生招生与培养

近三年来,本人指导研究生获得 北京图象图形学学会优博论文提名奖1人/次,校级优秀博士论文 1人/次, 校级优秀硕士论文 6人/次;

近三年来,本人以通讯作者指导研究生发表 CCF A类会议论文 15篇(包括ICCV *2, AAAI *6, IJCAI *3, ACM MM *3, ACM SIGKDD *1),IEEE/ACM Trans汇刊论文 14篇(包括IEEE TKDE *1, ACM TKDD *4, IEEE TMM *2, IEEE TCSVT *2, IEEE TCYB *2, ACM TIST *3);

(A) 本人年招收博士研究生(直博/硕博连读/申请考核:每年1名)!欢迎 数学 / 信息与计算科学 / 计算机科学与技术等专业同学邮件咨询!  

欢迎詹天佑学院的同学们联系!

(B) 本人常年招收硕士研究生(3-4名)!欢迎 数学 / 信息与计算科学 / 计算机科学与技术相关专业的同学报考!

期望:1. 热爱科研,并有志于发表高水平论文(领域内的CCF A类系列会议IEEE/ACM Trans系列汇刊);

          2. 良好的数学基础/英文读写/编程能力(上述能力都是可以培养的);

          3. 2024年尚有3个硕士名额,欢迎考研的同学们邮件联系

在读研究生

博士研究生:  

  • Yanan Wu (2019-,申请考核, ICCV*1AAAI*2, IJCAI*1, IEEE Trans. on CSVT*2, IET CV*1)       
  • Zhibin Gu (2020-,申请考核, ACM Trans. on KDD*2, APIN*1) 
  • Jing Wang (2022-,申请考核, AAAI*1, ACM Multimedia*1)
  • Yang Zhang (2023-,硕博连读, ACM Multimedia*1)
  • Jiacheng Li (2024-,  詹天佑学院本博连读)

全日制硕士研究生:    

  • Jintian Ji (2022-, 国家奖学金ICCV*1, ACM Multimedia*1), Tingting Wu (2022-, AAAI*1), Jing Liang (2022-), Hongtao Yang (2022-) 
  • Zhendong Li (2023-), Xudong Yan (2023-), Xiaoli Zhang (2023-)

毕业研究生

博士:

  • 2022:吕庚育 (北京图象图形学学会优博论文提名奖 |校级优秀博士论文 | 知行奖学金, AAAI*1, IJCAI*1, ACM SIGKDD*1, IEEE TKDE*1, IEEE TCYB*2, ACM TIST*3, ECML-PKDD*1, INS*1, SOCO*1) - 北京工业大学,副教授(高聘教授)
  • 2021:孙利娟 (IEEE TMM*1, AAAI*1, KAIS*1, APIN*1, NEUCOM*1, PAKDD*1- 航天一院 

硕士:

  • 2023:  邓响 (校级优秀硕士论文 国家奖学金IEEE TMM*1); 刘威 (校级优秀硕士论文国家奖学金, APIN*1);孙伟华 (校级优秀硕士论文);张展;王佳艺;  胡睿婷 
  • 2022:  陆迅 (校级优秀硕士论文, ACM TKDD*2); 刘馨媛 (院级优秀硕士论文 | 国家奖学金, APIN*1);王绍凯 (院级优秀硕士论文, APIN*1);赵建国(APIN*1);周彤;任博伟
  • 2021:李子薇 (级优秀硕士论文 | 国家奖学金, IJCAI*1); 孙悦 (国家奖学金, ECML-PKDD*1)
  • 2020:李振东 (校级优秀硕士论文)叶苹;刘燕;季玲玲;李艳青
  • 2019:权洪林 (级优秀硕士论文, MTA*1);黄文英;黄维雪
  • 2018:王晓莹 (校级优秀硕士论文, MTA*1)
  • 2017:李敬伟孙健                           
  • 2016:罗骁原邢妍妍翟昱昊           
  • 2014:谢延涛

科研项目

       主持多项  国家自然科学基金项目 / 北京市自然科学基金项目 / 教育部博士点基金项目 / 博士后科学基金特别资助项目 / 基本科研业务费重点项目。 部分代表性主持科研项目列表如下:

  • 北京市自然科学基金面上项目:2024-2026,主持(在研
  • 基本科研业务费重点资助项目:2022-2025,主持(在研
  • 国家自然科学基金面上项目:2019-2022, 主持(已结题
  • 北京市自然科学基金面上项目:2020-2022, 主持(已结题
  • 基本科研业务费自由申报项目:2019-2021, 主持(已结题)
  • 国家自然科学基金面上项目:2015-2018, 主持(已结题)
  • 北京市自然科学基金面上项目:2016-2018, 主持(已结题)
  • 基本科研业务费自由申报项目:2014-2015, 主持(已结题)
  • 基本科研业务费自由申报项目:2012-2013, 主持(已结题)
  • 家自然科学基金青年项目:2012-2014, 主持(已结题)
  • 教育部博士点基金新教师类项目:2012-2014, 主持(已结题)
  • 基本科研业务费自由申报项目:2010-2011, 主持(已结题)
  • 中国博士后科学基金特别资助项目:2010-2011, 主持(已结题)
  • 中国博士后科学基金面上资助项目:2009-2010, 主持(已结题)
  • 国家自然科学基金面上项目:2010-2012, 合作单位主持(已结题)

论文/期刊

(^  表示作者均为本人指导的研究生 + 表示共同第一作者, *表示本人为通讯作者) 

2024:

  • Yanan Wu^Zhixiang Chi+, Yang Wang, Konstantinos Plataniotis, Songhe Feng*. Test-Time Domain Adaptation By Learning Domain-Aware Batch Normalization. AAAI, 2024. (CCF A类, Oral)
  • Tingting Wu^, Songhe Feng*.  Low-rank Kernel Tensor Learning for Incomplete Multi-View Clustering. AAAI, 2024. (CCF A类)
  • Jing Wang^, Songhe Feng*. SURER: Structure-Adaptive Unified Graph Neural Network for Multi-View Clustering. AAAI, 2024. (CCF A类)
  • Yanan Wu^Songhe Feng*Transformer Driven Matching Selection Mechanism for Multi-label Image Classification. IEEE Trans. on Circuits and Systems for Video Technology, 34(2), pp. 924-939, 2024. (CCF B类)

2023:

  • Jintian Ji^, Songhe Feng*. Anchor Structure Regularization Induced Multi-View Subspace Clustering via Enhanced Tensor Rank Minimization. ICCV, 2023. (CCF A类)
  • Yanan Wu^, Zhixiang Chi+, Yang Wang, Songhe Feng*. MetaGCD: Learning to Continually Learn in Generalized Category Discovery. ICCV, 2023. (CCF A类)
  • Jintian Ji^, Songhe Feng*. High-Order Complementarity Induced Fast Multi-View Clustering with Enhanced Tensor Rank Minimization. ACM Multimedia, 2023. (CCF A类)
  • Yang Zhang^, Songhe Feng*. Enhancing Domain-Invariant Parts for Generalized Zero-Shot Learning. ACM Multimedia, 2023. (CCF A类)
  • Jing Wang^, Songhe Feng*. Triple-Granularity Contrastive Learning for Deep Multi-View Clustering. ACM Multimedia, 2023. (CCF A类)
  • Yanan Wu^Tengfei Liang+, Songhe Feng*. MetaZSCIL: A Meta-Learning Approach for Generalized Zero-Shot Class Incremental Learning. AAAI, 2023. (CCF A类) 
  • Bing Li, Haina Qin, Weihua Xiong, Yangxi Li, Songhe Feng, Weiming Hu, Steven Maybank. Ranking-based Color Constancy with Limited Training Samples. IEEE Trans. on Pattern Analysis and Machine Intelligence, 45(10), pp. 12304-12320, 2023. (CCF A类)
  • Haobo Wang, Shilong Yang, Gengyu Lyu, Weiwei Liu, Tianlei Hu, Ke Chen, Songhe Feng, Gang Chen. Deep Partial Multi-Label  Learning with Graph Disambiguation. IJCAI, 2023. (CCF A类)
  • Yanan Wu^, Songhe Feng*. Semantic-Aware Graph Matching Mechanism for Multi-Label Image Recognition. IEEE Trans. on Circuits and Systems for Video Technology, 33(11), pp. 6788-6803, 2023. (CCF B类
  • Xiang Deng^Songhe Feng*. Beyond Word Embeddings: Heterogeneous Prior Knowledge Driven Multi-Label Image Classification. IEEE Trans. on Multimedia, pp. 4013-4025, 2023. (CCF B类)
  • Xun Lu^, Songhe Feng*. Distance-Preserving Embedding Bipartite Graph Multi-View Learning with Application to Multi-Label Classification. ACM Trans. on Knowledge Discovery from Data, 17(2), 19:1-21, 2023. (CCF B类)   
  • Xun Lu^Songhe Feng*.  Structure Diversity-Induced Anchor Graph Fusion for Multi-View Clustering. ACM Trans. on Knowledge Discovery from Data, 17(2), 17:1-18, 2023. (CCF B类) 
  • Zhibin Gu^Songhe Feng*. Individuality Meets Commonality: A Unified Graph Learning Framework for Multi-View Clustering. ACM Trans. on Knowledge Discovery from Data, 17(1), 7:1-21, 2023. (CCF B类)
  • Zhibin Gu^, Songhe Feng*. ONION: Joint Unsupervised Feature Selection and Robust Subspace Extraction for Graph-based Multi-View Clustering. ACM Trans. on Knowledge Discovery from Data, 17(5), 70:1-23, 2023. (CCF B类)   
  • Gengyu Lyu^, Songhe Feng*. Prior Knowledge Regularized Self-Representation Model for Partial Multi-Label Learning. IEEE Trans. on Cybernetics, 53(3), pp. 1618-1628, 2023. (CCF B)
  • Gengyu Lyu^Songhe Feng*. Redundant Label Learning via Subspace Representation and Global Disambiguation. ACM Trans. on Intelligent Systems and Technology, 14(1), 15:1-19, 2023.
  • Gengyu Lyu^, Songhe Feng*. Prior Knowledge Constrained Adaptive Graph Framework for Partial Label Learning. ACM Trans. on Intelligent Systems and Technology, 14(2), 25:1-16, 2023.
  • Wei Liu^Jiazheng Yuan*Gengyu Lyu^Songhe Feng*.  Label Driven Latent Subspace Learning for Multi-View Multi-Label Classification. Applied Intelligence, 53(1), pp. 3850-3863, 2023. 
  • Zhibin Gu^, Hongzhe Liu*, Songhe Feng*. Diversity Induced Consensus and Structured Graph Learning for Multi-View Clustering. Applied Intelligence, 53(5), pp. 12237-12251, 2023.
  • Qihao Zhao, Fan Zhang, Wei Hu, Songhe Feng, Jun Liu. OHD: An Online Category-aware Framework for Learning with Noisy Labels under Long-Tailed Distribution.  IEEE Trans. on Circuits and Systems for Video Technology, 2023. (CCF B类, Early Access)
  • Zheming Xu, Lili Wei, Congyan Lang, Songhe Feng, Tao Wang, Adrian G. Boris, Hongzhe Liu. SSR-Net: A Spatial Structure Relation Network for Vehicle Re-Identification. ACM Trans. on Multimedia Computing, Communication, and Applications, 19(6): 1-22, 2023. (CCF B类)
  • Yutong Gao, Liqian Liang, Congyan Lang, Songhe Feng, Yidong Li, Yunchao Wei. Clicking Matters: Towards Interactive Human Parsing. IEEE Trans. on Multimedia, pp. 3190-3203, 2023. (CCF B类)

2022:

  • Gengyu Lyu^, Yanan Wu^, Songhe Feng*. Deep Graph Matching for Partial Label Learning. IJCAI, pp. 3306-3312, 2022. (CCF A类)
  • Gengyu Lyu^, Xiang Deng^, Yanan Wu^Songhe Feng*. Beyond Shared Subspace: A View-Specific Fusion for Multi-View Multi-Label Learning. AAAI, pp. 7647-7654, 2022. (CCF A类)
  • Lijuan Sun^Songhe Feng*. Global-Local Label Correlation for Partial Multi-Label Learning. IEEE Trans. on Multimedia, 24(2), pp. 581-593, 2022(CCF B类)
  • Gengyu Lyu^, Songhe Feng*. A Self-paced Regularization Framework for Partial-Label Learning. IEEE Trans. on Cybernetics, 52(2), pp. 899-911, 2022(CCF B类)  
  • Shaokai Wang^, Mingxuan Xia#, Zilong Wang#, Gengyu Lyu^, Songhe Feng*. Partial Label Learning with Noisy Side Information. Applied Intelligence, 52(11), pp. 12382-12396, 2022. 
  • Xinyuan Liu^, Lijuan Sun^, Songhe Feng*. Incomplete Multi-View Partial Multi-Label Learning. Applied Intelligence, 52(3), pp. 3289-3302, 2022.
  • Jianguo Zhao^, Gengyu Lyu^, Songhe Feng*. Linear Neighborhood Reconstruction Constrained Latent Subspace Discovery for Incomplete Multi-View Clustering. Applied Intelligence, 52(1), pp. 982-993, 2022.
  • Tengfei Liang, Yi Jin, Wu Liu, Songhe Feng, Tao Wang, Yidong Li. Keypoint-Guided Modality-Invariant Discriminative Learning for Visible-Infrared Person Re-Identification. ACM Multimedia, 2022. (CCF A类) 
  • Gongpei Zhao, Tao Wang, Yidong Li, Yi Jin, Congyan Lang, Songhe Feng. Neighborhood Pattern is Crucial for Graph Convolutional Networks Performing Node Classification. IEEE Trans. on Neural Networks and Learning System. 2022. (CCF B类, Early Access)
  • Liqian Liang, Congyan Lang, Zun Li, Jian Zhao, Tao Wang, Songhe Feng. Seeing Crucial Parts: Vehicle Model Verification via A Discriminative Representation Model. ACM Trans. on Multimedia Computing, Communication, and Applications, 18(1), pp. 1-22, 2022. (CCF B类) 
  • Zun Li, Congyan Lang, Liqian Liang, Jian Zhao, Songhe Feng, Qibin Hou, Jiashi Feng. Dense Attentive Feature Enhancement for Salient Object Detection. IEEE Trans. on Circuits and Systems for Video Technology, 32(12), pp. 8128-8141, 2022. (CCF B类  
  • Lili Wei, Congyan Lang, Liqian Liang, Songhe Feng, Tao Wang, Shidi Chen. Weakly-Supervised Video Object Segmentation via Dual-Attention Cross-Branch Fusion. ACM Trans. on Intelligent Systems and Technology, 13(3), pp.1-20, 2022 
  • Xiuting You, He Liu, Tao Wang, Songhe Feng, Congyan Lang. Object Detection by Crossing Relational Reasoning based on Graph Neural Network. Machine Vision and Applications, 2022
  • Shi Qiu, Yi Jin, Songhe Feng, Tao Zhou, Yidong Li. Dwarfism Computer-Aided Diagnosis Algorithm based on Multimodal Pyradiomics. Information Fusion, pp. 137-145, 2022. 
  • Ruijie Zhao, Congyan Lang, Zun Li, Liqian Liang, Lili Wei, Songhe Feng, Tao Wang. Pedestrain Attribute Recognition based on Attribute Correlation. Multimedia System, pp. 1069-1081, 2022. 
  • Yichen Zhu, Lili Wei, Congyan Lang, Siyu Li, Songhe Feng, Yidong Li. Fine-Grained Facial Expression Recognition via Relational Reasoning and Hierarchical Relation Optimization. Pattern Recognition Letters, 2022.

2021:

  • Yanan Wu^, He Liu+Songhe Feng*. GM-MLIC: Graph Matching based Multi-Label Image Classification. IJCAI, pp. 1179-1185, 2021. (CCF A类)   
  • Gengyu Lyu^, Songhe Feng*. GM-PLL: Graph Matching based Partial Label Learning.  IEEE Trans. on Knowledge and Data Engineering, 33(2), pp. 521-535, 2021(CCF A类)
  • Lijuan Sun^, Songhe Feng*. Partial Multi-Label Learning with Noisy Side Information. Knowledge and Information Systems, 63(2), pp. 541-564, 2021. (CCF B类)
  • Gengyu Lyu^, Songhe Feng*. Noisy Label Tolerance: A New Perspective of Partial Multi-Label Learning. Information Sciences, 543(1), pp. 454-466, 2021. (CCF B类)
  • Lijuan Sun^, Gengyu Lyu^, Songhe Feng*. Beyond Missing: Weakly-Supervised Multi-Label Learning with Incomplete and Noisy Labels, Applied Intelligence, 51(3), pp. 1552-1564, 2021. 
  • Yanan Wu^, Songhe Feng*. L4Net: An Anchor-Free Generic Object Detector with Attention Mechanism for Autonomous Driving. IET Computer Vision, 15(1), pp. 36-46, 2021. 
  • Tong Zhou^, Songhe Feng*. Multiple Semantic Embedding with Graph Convolutional Networks for Multi-Label Image Classification. PRCV, 2021. 
  • Liqian Liang, Congyan Lang, Yidong Li, Songhe Feng, Jian Zhao. Fine-Grained Facial Expression Recognition in the Wild. IEEE Trans. on Information Forensics and Security, 16(1), pp. 482-494, 2021. (CCF A类) 
  • Min Wang, Congyan Lang, Liqian Liang, Songhe Feng, Tao Wang, Yutong Gao. Fine-Grained Semantic Image Synthesis with Object Attention Generative Adversarial Network. ACM Trans. on Intelligent Systems and Technology, 12(5), pp. 1-18, 2021 
  • Min Wang, Congyan Lang, Songhe Feng, Tao Wang, Yi Jin, Yidong Li. Text to Photo-Realistic Image Synthesis via Chained Deep Recurrent Generative Adversarial Network. Journal of Visual Communication ans Image Representation, 74(1), 2021. 
  • Min Wang, Congyan Lang, Liqian Liang, Gengyu Lyu, Songhe Feng, Tao Wang. Class-balanced Text to Image Synthesis with Attentive Generative Adversarial Network. IEEE Multimedia, 28(3), pp. 21-31, 2021.

2020: 

  • Gengyu Lyu^, Songhe Feng. Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism. ACM SIGKDD, pp. 105-113, 2020. (Research Track, CCF A)
  • Ziwei Li^, Gengyu Lyu^, Songhe Feng*. Partial Multi-Label Learning via Multi-Subspace Representation. IJCAI, pp. 2612-2618, 2020. (CCF A) 
  • Gengyu Lyu^, Songhe Feng*. HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization. ACM Trans. on Intelligent Systems and Technology, 11(3), 34: 1-34:19, 2020. 
  • Gengyu Lyu^, Songhe Feng*. Partial Label Learning via Self-Paced Curriculum Learning, ECML-PKDD, pp. 489-505, 2020. (CCF B类)     
  • Yue Sun^, Gengyu Lyu^, Songhe Feng*. Partial Label Learning via Subspace Representation and Global Disambiguation, ECML-PKDD, pp. 439-454, 2020. (CCF B类) 
  • Lijuan Sun^, Ping Ye^, Gengyu Lyu^, Songhe Feng*. Weakly-Supervised Multi-Label Learning with Noisy Features and Incomplete Labels. Neurocomputing, 413(6), pp. 61-71, 2020.
  • Gengyu Lyu^, Songhe Feng*. Partial Label Learning via Low-Rank Representation and Label Propagation. Soft Computing, pp. 5165-5176, 2020
  • Honglin Quan^, Songhe Feng*. Improving Person Re-identification via Attribute-identity Representation and Visual Attention Mechanism. Multimedia Tools and Applications, 79(11-12), pp. 7259-7278, 2020. 
  • Min Wang, Congyan Lang, Liqian Liang, Yutong Gao, Songhe Feng, Tao Wang. End-to-End Text-to-Image Synthesis with Spatial Constraints. ACM Trans. on Intelligent Systems and Technology, 11(4): 47:1-47:19, 2020.
  • Min Wang, Congyan Lang, Liqian Liang, Gengyu Lyu, Songhe Feng, Tao Wang. Attentive Generative Adversarial Network to Bridge Multi-Domain Gap for Image Synthesis. ICME, pp, 1-6, 2020. (CCF B类)
  • Zhongyi Li, Yi Ji, Yidong Li, Congyan Lang, Songhe Feng, Tao Wang.  Learning Part-Alignment Feature for Person Re-Identification with Spatial Temporal based Re-ranking Method. World Wide Web, 23(3), pp. 1907-1923, 2020. (CCF B)  
  • Zhenxing Zheng, Zhendong Li, Gaoyun An, Songhe Feng. Subgraph and Object Context-Masked Network for Scene Graph Generation. IET Computer Vision, 14(7), pp. 546-553, 2020. 
  • Yingxia Jia, Congyan Lang, Songhe Feng. A Semantic Segmentation Method of Traffic Scene Based on Categries-Aware Domain Adaption. Journal of Computer Research and Development, 2020. (In Chinese)  
  • Zheming Xu, Lili Wei, Congyan Lang, Songhe Feng, Tao Wang, Adrian G Bors. HSS-GCN: A Hierarchical Spatial Structure Graph Convolutional Network for Vehicle Re-Identification. ICPR, 2020.  

2019:

  • Lijuan Sun^, Songhe Feng*. Partial Multi-Label Learning by Low-Rank and Sparse Decomposition. AAAI, 2019. (CCF A)
  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng, Xiaohui Hou. Deformable Surface Tracking by Graph Matching. ICCV, 2019. (CCF A)      
  • Xiaoying Wang^, Songhe Feng*. Semi-Supervised Dual Low-Rank Feature Mapping for Multi-Label Image Annotation.  Multimedia Tools and Applications, 78(10), pp. 13149-13168, 2019. 
  • Lijuan Sun^, Songhe Feng*. Robust Semi-Supervised Multi-Label Learning by Triple Low-Rank Regularization. PAKDD, 2019. 
  • Zun Li, Congyan Lang, Jiashi Feng, Yidong Li, Tao Wang, Songhe Feng. Co-Saliency Detection with Graph MatchingACM Trans. on Intelligent System and Technology, 10(3), 22:1-22:22, 2019. 
  • Yanan Dong, Congyan Lang, Songhe Feng*. General Structured Sparse Learning for Human Facial Age Estimation. Multimedia Systems, 25(1), pp. 49-57, 2019. 
  • Mengxia Yin, Congyan Lang, Zun Li, Songhe Feng, Tao Wang. Recurrent Convolutional Network for Video-based Smoke Detection. Multimedia Tools and Applications, 78(1), pp. 237-256, 2019. 
  • Bingqian Geng, Congyan Lang, Junliang Xing, Songhe Feng. MFAD: A Multi-modality Face Anti-spoofing Dataset. PRICAI, 2019. 
  • Ping Ye^, Songhe Feng*. Robust Multi-Label Learning with Corrputed Features and Incomplete Labels. CAC, 2019.       

Earlier:

  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng. Graph Matching with Adaptive and Branching Path Following.  IEEE Trans. on Pattern Analysis and Machine Intelligence, 40(12), pp. 2853-2867, 2018. (CCF A) 
  • Songhe Feng, Congyan Lang. Graph Regularized Low-rank Feature Mapping for Multi-label Learning with Application to Image Annotation. Multidimensional Systems and Signal Processing, 29, pp. 1351-1372, 2018. 
  • Wenying Huang^, Songhe Feng*. Partial Label Learning via Low-rank Representation and Label Propagation. ICIMCS, 2018.  
  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng. Constrained Confidence Matching for Planar Object Tracking. ICRA, 2018. (CCF B)   
  • Zun Li, Congyan Lang, Songhe Feng, Tao Wang. Saliency Ranker: A New Salient Object Detection Method.  Journal of Visual Communication and Image Representation, 50(1), pp. 16-26, 2018.  
  • Jun Zhou, Tao Wang, Congyan Lang, Songhe Feng. A Novel Hypergraph Matching Algorithm based on Tensor Refining. Journal of Visual Communication and Image Representation, 57, pp. 69-75, 2018. 
  • Shaoyan Xu, Tao Wang, Congyan Lang, Songhe Feng, Yi Jin. Graph-based Visual Odometry for VSLAM. Industrial Robot, 2018.
  • Songhe Feng, Congyan Lang, Jiashi Feng, Tao Wang, Jiebo Luo. Human Facial Age Estimation by Cost-Sensitive Label Ranking and Trace Norm Regularization. IEEE Trans. on Multimedia, 19(1), pp. 136-148, 2017. (CCF B)
  • Zhu Teng, Junliang Xing, Qiang Wang, Congyan Lang, Songhe Feng, Yi Jin. Robust Object Tracking Based on Temporal and Spatial Deep Networks. ICCV, 2017. (CCF A)   
  • Congyan Lang, Jiashi Feng, Songhe Feng, Jingdong Wang, Shuicheng Yan. Dual Low-Rank Pursuit: Learning Salient Features for Saliency Detection.  IEEE Trans. On Neural Networks and Learning Systems, 27(6), pp. 1190-1200, 2016. (CCF B)  
  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng. Symmetry-Aware Graph Matching. Pattern Recognition, 60, pp. 657-668, 2016. (CCF B 
  • Jingwei Li^, Songhe Feng*. Graph Regularized Low-rank Feature Learning for Robust Multi-Label Image Annotation. ICSP, 2016.
  • Songhe Feng, Zheyun Feng, Rong Jin. Learning to Rank Image Tags with Limited Training Examples. IEEE Trans. on Image Processing,  24(4), pp. 1223-1234, 2015. (CCF A)
  • Chenjing Yan, Congyan Lang, Songhe Feng. Facial Age Estimation Based on Structured Low-rank Representation. ACM Multimedia, 2015. (CCF A)  
  • Xiaoyuan Luo^, Songhe Feng*. A General Method for Sensitive Identification Detection in the Terrorist Video. ICIMCS, 2015.
  • Tao Wang, Hua Yang, Congyan Lang, Songhe Feng. An Error-Tolerant Approximate Matching Algorithm for Labeled Combinational Maps. Neurocomputing, 156(25). pp. 211-220, 2015.
  • Zheyun Feng, Songhe Feng, Rong Jin, A. K. Jain. Image Tag Completion by Noisy Matrix Recovery. ECCV, 2014. (CCF B)
  • Songhe Feng, Weihua Xiong. Hierarchical Sparse Representation based Multi-Instance Semi-Supervised Learning with Application to Image Categorization. Signal Processing, 94(1), pp.595-607, 2014.  
  • Songhe Feng, Congyan Lang. Adaptive All-Season Image Tag Ranking by Saliency-Driven Image Pre-Classification. Journal of Visual Communication and Image Representation, 24(7),  pp.1031-1039. 2013. 
  • Congyan Lang, Songhe Feng. Supervised Sparse Patch Coding Towards Misalignment-Robust Face Recognition. Journal of Visual Communication and Image Representation, 24(2): 103-110, 2013. 
  • Songhe Feng, Congyan Lang, Bing Li. Towards Relevance and Saliency Ranking of Image Tags. ACM Multimedia, 2012. (CCF A)  
  • Bing Li, Songhe Feng. Scaring or Pleasing: Exploit Emotional Impact of an Image. ACM Multimedia, 2012. (CCF A ) 
  • Songhe Feng, Hong Bao. Combining Visual Attention Model with Multi-instance Learning for Tag Ranking. Neurocomputing, 74(2011). pp. 3619-3627. 
  • Songhe Feng, Congyan Lang. Combining Graph Learning and Region Saliency Analysis for Content-based Image Retrieval. Chinese Journal of Electronics, 39(10), pp. 2287-2294, 2011. (In Chinese)
  • Shuoyan Liu, De Xu, Songhe Feng. Region Contextual Visual Words for Scene Classification. Expert Systems with Applications, 11591-11597, 2011. 
  • Hong Bao, Songhe Feng. A Novel Saliency-based Graph Learning Framework with Application to CBIR. IEICE Trans. on Information System, 94(6), pp. 1353-1356, 2011.
  • Songhe Feng, Congyan Lang, De Xu. Beyond Tag Relevance: Integrating Visual Attention Model and Multi-Instance Learning for Tag Saliency Ranking. ACM CIVR, 2010. (CCF B类)
  • Songhe Feng, De Xu. Transductive Multi-Instance Multi-Label Learning Algorithm with Application to Automatic Image Annotation. Expert Systems with Applications37(1), pp. 661-670, Jan.2010. 
  • Songhe Feng, De Xu. Attention-driven Salient Edge(s) and Region(s) Extraction with Application to CBIR. Signal Processing, 90(1), pp.1-15, 2010. 
  • Shuoyan Liu, De Xu, Songhe Feng. Discriminating Semantic Visual Words for Scene Classification. IEICE Trans. on Information System, 93(6), pp. 1580-1588, 2010.     
  • Songhe Feng, De Xu. Combining Attention Model with Hierarichical Graph Representation for Region-based Image Retrieval. IEICE Trans. on Information System, 91(8), pp. 2203-2206, 2008. 
  • Songhe Feng, De Xu. Automatic Image Annotation Using An Improved Multiple-Instance Learning Algorithm. Chinese Journal of Electronics, 17(1), pp. 43-47,2008. 
  • Songhe Feng, De Xu. Automatic Image Annotation using Semi-Supervised Multi-Instance Multi-Label Learning Algorithm. Chinese Journal of Electronics, 17(4), pp. 602-606, 2008. 
  • Songhe Feng, De Xu. A Novel Graph Kernel Based SVM Algorithm for Image Semantic Retrieval. ISNN, 2016.
  • Songhe Feng, De Xu. Locating Salient Edges for CBIR Based on Visual Attention Model. ICNC, 2006. 
  • Songhe Feng, De Xu. A Novel Region-based Image Retrieval Algorithm Using Selective Visual Attention Model. ACIVS, 2005.

招生专业

  • 计算机科学与技术硕士
  • 计算机技术硕士
  • 软件工程硕士
  • 人工智能硕士
  • 网络与信息安全硕士
  • 大数据技术与工程硕士
  • 计算机科学与技术博士
  • 计算机技术博士
  • 人工智能博士

教学工作

承担本科生课程:

  • 高级程序设计语言(詹天佑学院基础课程);    

承担研究生课程:

  • 机器视觉基础 (硕士生专业基础课程);
  • 视觉认知计算与图像语义计算 (博士生课程);

指导大学生本科创新训练项目:

  • 不完整多视图聚类算法关键技术研究(周子豪、张绍琪,2022年, 国家
  • 多视图偏多标记学习算法研究(张珂镨、刘滨畅、李振东,2021年,国家级
  • 偏标记学习算法研究(王子龙、陈钎源、夏明轩,2019年,国家级
  • 基于属性特征的视频行人再识别算法研究(姚可欣、修宇婷、刘欢,2018年,国家级

专利

  • 基于多子空间表示的偏多标记学习算法;专利号:202010412162.1
  • 基于全局和局部标记关系的偏多标记学习算法;专利号:202010411579.6
  • 特征信息存在噪声的偏多标记学习算法;专利号:202010411580.9;
  • 基于噪声容忍的偏多标记算法;专利号:202010412161.7;
  • 基于子空间表示和全局标记消歧的偏标记学习算法;专利号:202010397386.X;

获奖与荣誉

  • 2023年度,北京图象图形学学会优秀导师提名奖;
  • 2021年度,北京交通大学计算机学院师德师风先进个人(研途领航);
  • 2020年度,北京交通大学"三育人"先进个人;
  • 2014年度,北京交通大学首批青年英才计划II类人选(2015-2017);
  • 2011年度,北京交通大学握奇奖教金;
  • 2010年度,北京交通大学计算机学院教学基本功比赛一等奖;

社会兼职

  • 北京市信息服务工程市重点实验室第三届学术委员会委员(2020-2022);
  • Senior Program Committee Member: AAAI(2022);
  • Program Committee Member: CVPR(2024), NeurIPS(2021-2023), ICML(2021, 2023), KDD(2023), AAAI(2019-2024), IJCAI(2019, 2020); 
  • Journal Reviewer for : IEEE Trans. on PAMI, IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, IEEE Trans. on NNLS, IEEE Trans. on Cybernetics, IEEE Trans. on Big Data, ACM Trans. on Knowledge Discovery for Data;