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科学与技术学院9号教学楼北524 邮编：100044

个人简介

       北京交通大学计算机科学与技术学院教授，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。主要研究领域为多模态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2项。在包括 IEEE TPAMI, IEEE TIP, IEEE TKDE, ACM TKDD, IEEE TMM, IEEE TCSVT, IEEE TCYB, IEEE TNNLS 等知名学术期刊以及 ICML, NeurIPS, 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，计算机科学与技术学院，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

聚焦于多模态机器学习及在开放场景下跨域图像语义理解研究，包括但不限于：Multi-View Clustering/Classification、Compositional Zero-Shot Learning、Test-Time Domain Adaptation、Few-Shot Learning、Novel Category Discovery、Composed Image Retrieval等；

研究生招生与培养

近五年来，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 7人/次，国家奖学金 10人/次；
  • 发表 CCF A类会议论文 25 篇 (ICML*1, NeurIPS*1, CVPR*1, ICCV*2, ACM SIGKDD*3, AAAI*8，IJCAI*6，ACM MM*3)；
  • 发表 IEEE/ACM Trans论文 17 篇 (IEEE TPAMI*1, IEEE TKDE*1, ACM TKDD*5, IEEE TNNLS*1, IEEE TMM*2, IEEE TCSVT*2, IEEE TCYB*2, ACM TIST*3)；

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

欢迎詹天佑学院的同学们联系！

(B) 本人拟招收参加统考的2025届硕士研究生(2-3名)！欢迎 计算机科学与技术/ 数学 / 信息与计算科学 相关专业具有推免资格的同学跟我邮件联系！

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

          2. 良好的数学基础/英文读写/编程能力；

          3. 善于沟通与合作；

在读研究生

博士研究生:  

  • 王   靖 (2022-，申请考核, 国家奖学金 | CVPR*1, AAAI*1, IJCAI*1, ACM MM*1)
  • 张   阳 (2023-，硕博连读, IJCAI*1, ACM MM*1)
  • 李嘉诚 (2024-,  詹天佑学院直博)
  • 朱   臻 (2024-,  定向普博)
  • 闫旭东 (2025-, 硕博连读)

全日制硕士研究生:    

  • 季津天 (2022-, 国家奖学金*2 | IEEE TPAMI*1, ICCV*1, KDD*1, ACM MM*1, Neural Networks*1), 吴婷婷 (2022-, 国家奖学金 | AAAI*2)
  • 李振东 (2023-, ICML*1(Co-Author), KDD*1(Co-Author), AAAI*1(Co-First Author)), 张晓丽 (2023-)
  • 时伟东 (2024-), 左臣 (2024-), 温昊楠 (2024-)

毕业研究生

博士：

  • 2024：谷志斌 (ICML*1, NeurIPS*1, KDD*1, ACM TKDD*3, APIN*2) - 河北师范大学，校特聘副教授
  • 2024：吴亚楠 (ICCV*1, AAAI*2, IJCAI*1, IEEE TCSVT*2, IET CV*1) - Carleton University，Canada, 博士后       
  • 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) - 北京工业大学，副教授
  • 2021：孙利娟 (IEEE TMM*1, AAAI*1, KAIS*1, APIN*1, NEUCOM*1, PAKDD*1) - 航天一院(sunlijuan@bupt.edu.cn) 

硕士：

  • 2024：梁婧 (校级优秀硕士论文); 杨洪涛
  • 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 (院级优秀硕士论文 | 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 (院级优秀硕士论文); 黄文英; 黄维雪
  • 2018：王晓莹 (校级优秀硕士论文)
  • 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（已结题）
  • 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）
  • 国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， * 表示本人为通讯作者) 

2025:

  • Jintian Ji^, Songhe Feng*. Anchors Crash Tensor: Efficient and Scalable Tensorial Multi-View Subspace Clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2025. (CCF A类, Early Access)

  • Tingting Wu^, Zhendong Li^, Zhibin Gu^, Jiazheng Yuan, Songhe Feng*. KOALA: Kernel Coupling and Element Imputation Induced Multi-View Clustering. AAAI, 2025. (CCF A类)

  • Gengyu Lyu^, Bohang Sun, Xiang Deng^, Songhe Feng*. Addressing Multi-Label Learning with Partial Labels: from Sample Selection to Label Selection. AAAI, 2025. (CCF A类)

  • Jintian Ji^, Songhe Feng*. Partition-Level Fusion Induced Multi-View Subspace Clustering with Tensorial Geman Rank. Neural Networks, 182(2), pp. 1-13, 2025. (CCF B类)

2024:

  • Zhibin Gu^, Songhe Feng*. From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement. NeurIPS, 2024. (CCF A类)
  • Zhibin Gu^, Zhendong Li^, Songhe Feng*. EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Rank Error Minimization. ICML, 2024. (CCF A类)
  • Zhibin Gu^, Zhendong Li^, Songhe Feng*. Topology-Driven Multi-View Clustering via Tensorial Refined Sigmoid Rank Minimization. ACM SIGKDD, 2024. (Research Track, CCF A类)
  • Jintian Ji^, Songhe Feng, Yidong Li*. Tensorized Unaligned Multi-view Clustering with Multi-scale Representation Learning. ACM SIGKDD, 2024. (Research Track, CCF A类)
  • Jing Wang^, Songhe Feng*. Contrastive and View-Interaction Structure Learning for Multi-View Clustering. IJCAI, 2024. (CCF A类)
  • Yang Zhang^, Songhe Feng*, Jiazheng Yuan*. Continual Compositional Zero-Shot Learning. IJCAI, 2024. (CCF A类)
  • Gengyu Lyu^, Weiqi Kang, Haobo Wang, Zheng Li, Zhen Yang*, Songhe Feng*. Common-Individual Semantic Fusion for Multi-View Multi-Label Learning. IJCAI, 2024. (CCF A类)
  • 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*, Jiazheng Yuan*. Low-rank Kernel Tensor Learning for Incomplete Multi-View Clustering. AAAI, 2024. (CCF A类)

  • Jing Wang^, Songhe Feng*, Gengyu Lyu, Jiazheng Yuan. SURER: Structure-Adaptive Unified Graph Neural Network for Multi-View Clustering. AAAI, 2024. (CCF A类)

  • Gengyu Lyu^, Zhen Yang*, Xiang Deng^, Songhe Feng*.  L-VSM: Label Driven View-Specific Fusion for Multi-View Multi-Label Classification. IEEE Trans. on Neural Networks and Learning Systems, 2024. (CCF B类, Early Access)

  • Yanan Wu^, Songhe Feng*, Gongpei Zhao, Yi Jin. 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)
  • Zhibin Gu^, Songhe Feng*, Zhendong Li, Jiazheng Yuan*, Jun Liu. NOODLE: Joint Cross-View Discrepancy Discovery and High-Order Correlation Detection for Multi-View Subspace Clustering. ACM Trans. on Knowledge Discovery from Data, 18(6), 151:1-23, 2024. (CCF B类)
  • Zhibin Gu^, Songhe Feng*, Jiazheng Yuan*, Ximing Li. Consensus Representation-Driven Structured Graph Learning for Multi-View Clustering. Applied Intelligence, 54(6), pp. 8545-8562, 2024.
  • 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, 34(5), pp. 3806-3818, 2024. (CCF B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 Systems, 35(6), pp. 8456-8469, 2024. (CCF B类)
  • Tengfei Liang, Yi Jin*, Wu Liu, Tao Wang, Songhe Feng, Yidong Li. Bridging the Gap: Multi-Level Cross-Modality Joint Alignment for Visible-Infrared Person Re-Identification. IEEE Trans. on Circuits and Systems for Video Technology, 2024. (CCF B类，Early Access)
  • He Liu, Tao Wang*, Congyan Lang, Songhe Feng, Yi Jin, Yidong Li. GLAN: A Graph-based Linear Assignment Network. Pattern Recognition, 2024. (CCF B类, Early Access)

2023:

  • 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)
  • 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*, Gengyu Lyu, Zhibin Gu. Triple-Granularity Contrastive Learning for Deep Multi-View Clustering. ACM Multimedia, 2023. (CCF A类)
  • Yanan Wu^, Tengfei Liang+, Songhe Feng*. Yi Jin, Gengyu Lyu, Haojun Fei, Yang Wang. MetaZSCIL: A Meta-Learning Approach for Generalized Zero-Shot Class Incremental Learning. AAAI, 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*, Yang Wang. 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*, Gengyu Lyu, Tao Wang, Congyan Lang. 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*, Gengyu Lyu, Yi Jin, Congyan Lang. 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*, Huiting Hu, Gengyu Lyu. 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*, Yi Jin, Tao Wang, Congyan Lang, Yidong Li. Prior Knowledge Regularized Self-Representation Model for Partial Multi-Label Learning. IEEE Trans. on Cybernetics, 53(3), pp. 1618-1628, 2023. (CCF B类)
  • Gengyu Lyu^, Songhe Feng*, Wei Liu, Shuoyan Liu, Congyan Lang. 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*, Shaokai Wang, Zhen Yang. 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.
  • 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*, Jun Liu, Gengyu Lyu, Congyan Lang. 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*, Tao Wang, Congyan Lang. 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) 
  • 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*, Yi Jin, Gengyu Lyu, Zizhang Wu. GM-MLIC: Graph Matching based Multi-Label Image Classification. IJCAI, pp. 1179-1185, 2021. (CCF A类)   
  • Gengyu Lyu^, Songhe Feng*, Tao Wang*, Congyan Lang, Yidong Li. 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*, Gengyu Lyu, Hua Zhang, Guojun Dai. 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*, Yidong Li. 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, Yidong Li*. Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism. ACM SIGKDD, pp. 105-113, 2020. (Research Track, CCF A类)
  • Ziwei Li^, Gengyu Lyu^, Songhe Feng*. Partial Multi-Label Learning via Multi-Subspace Representation. IJCAI, pp. 2612-2618, 2020. (CCF A类) 
  • Gengyu Lyu^, Songhe Feng*, Yidong Li, Yi Jin, Guojun Dai, Congyan Lang. 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类)  
  • 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*, Tao Wang, Congyan Lang, Yi Jin. Partial Multi-Label Learning by Low-Rank and Sparse Decomposition. AAAI, 2019. (CCF A类)
  • Tao Wang, Haibin Ling*, Congyan Lang, Songhe Feng, Xiaohui Hou. Deformable Surface Tracking by Graph Matching. ICCV, 2019. (CCF A类)      
  • 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 Matching. ACM 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.     

2018 and Before:

  • 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类) 
  • 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. 
  • Tao Wang, Haibin Ling*, Congyan Lang, Songhe Feng. Constrained Confidence Matching for Planar Object Tracking. ICRA, 2018. (CCF B类)   
  • 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. 
  • 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类)
  • 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类)   
  • 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类)  
  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng. Symmetry-Aware Graph Matching. Pattern Recognition, 60, pp. 657-668, 2016. (CCF B类)  
  • 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类)
  • Chenjing Yan, Congyan Lang*, Songhe Feng. Facial Age Estimation Based on Structured Low-rank Representation. ACM Multimedia, 2015. (CCF A类)    
  • 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类)
  • 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类)  
  • Bing Li, Songhe Feng. Scaring or Pleasing: Exploit Emotional Impact of an Image. ACM Multimedia, 2012. (CCF A类) 
  • 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 Applications, 37(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.   

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
  • 大数据技术与工程硕士
  • 计算机科学与技术博士
  • 人工智能博士
  • 新一代电子信息技术（含量子技术等）硕士
  • 软件工程博士
  • 计算机技术博士
  • 新一代电子信息技术（含量子技术等）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, 国家级）
  • 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(2021-2024), ICML(2021-2024), 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；