冯松鹤

基本信息

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

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 24 篇 (ICML*1, NeurIPS*1, ICCV*2, ACM SIGKDD*3, AAAI*8，IJCAI*6，ACM MM*3)；
• 发表 IEEE/ACM Trans论文 16 篇 (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 | 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)

全日制硕士研究生:    

• 季津天 (2022-, 国家奖学金*2 | 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)), 闫旭东 (2023-), 张晓丽 (2023-)
• 时伟东 (2024-), 左臣 (2024-), 温浩楠 (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（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）
• 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， + 表示共同第一作者， *表示通讯作者) 

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. 
• 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. 
• 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. 
• 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)  
• 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类)
• Chenjing Yan, Congyan Lang*, Songhe Feng. Facial Age Estimation Based on Structured Low-rank Representation. ACM Multimedia, 2015. (CCF A类)  
• 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. 
• 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.