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Correspondence
Mail: School of Computer Science and Engineering,
Jiulonghu Campus, Southeast University,
Nanjing 211189, China
Office: 516, Computer Science Building,
Jiulonghu Campus, Southeast University
Xin Geng
耿 新
Ph.D., Professor (东南大学首席教授,二级教授)
Email: xgeng AT seu.edu.cn
Tel: +86-25-52090876
Fax: +86-25-52090876
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Research Interests
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Selected Publications
Journal Articles
2022
- X. Geng, X. Qian, Z. Huo, and Y. Zhang. Head Pose Estimation Based on Multivariate Label Distribution. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2022, 44(4): 1974-1991.
- K. Smith-Miles and X. Geng. Revisiting Facial Age Estimation with New Insights from Instance Space Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2022, 44(5): 2689-2697.
- N. Xu, J. Li, Y.-P. Liu, and X. Geng. Trusted-Data-Guided Label Enhancement on Noisy Labels. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2022, in press.
- L. Qi, L. Wang, J. Huo, Y. Shi, X. Geng, and Y. Gao. Adversarial Camera Alignment Network for Unsupervised Cross-camera Person Re-identification. IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2022, 32(5): 2921-2936..
- Y. Ren, N. Xu, M. Ling, and X. Geng. Label Distribution for Multimodal Machine Learning. Frontiers of Computer Science (FCS), 2022, 16: 161306.
- M. Zhang, N. Xu, and X. Geng. Feature-Induced Label Distribution for Learning with Noisy Labels. Pattern Recognition Letters (PRL), 2022, 155: 107-113.
2021
- X. Geng, R. Zheng, J. Lv, and Y. Zhang. Multilabel Ranking with Inconsistent Rankers. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021, in press.
- J. Wang, X. Geng and H. Xue. Re-weighting Large Margin Label Distribution Learning for Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2021, in press.
- N. Xu, Y.-P. Liu and X. Geng. Label Enhancement for Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021, 33(4): 1632-1643.
- M.-L. Zhang, Q.-W. Zhang, J.-P. Fang, Y.-K. Li, and X. Geng. Leveraging Implicit Relative Labeling-Importance Information for Effective Multi-Label Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021, 33(5): 2057-2070.
- K. Wang, N. Xu, M. Ling, and X. Geng. Fast Label Enhancement for Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021, in press.
- C. Tan, S. Chen, G. Ji, and X. Geng. A Novel Probabilistic Label Enhancement Algorithm for Multi-label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021, in press.
- N. Xu, Y.-P. Liu, Y. Zhang, X. Geng. Progressive Enhancement of Label Distributions for Partial Multi-Label Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2021, in press.
- J. Wang and X. Geng. Label Distribution Learning by Exploiting Label Distribution Manifold. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2021, in press.
- J. Lv, T. Wu, C. Peng, Y. Liu, N. Xu, and X. Geng. Compact Learning for Multi-Label Classification. Pattern Recognition (PRJ), 2021, 113: 107833.
- H. Zhang, Y. Zhang, and X. Geng. Practical Age Estimation Using Deep Label Distribution Learning. Frontiers of Computer Science (FCS), 2021, 15(3): 153318.
2020
- C. Tan, G. Ji, X. Geng, .and S. Chen. A Novel Probabilistic Label Enhancement Algorithm for Multi-label Distribution Learning. IEEE Transactions on Cybernetics (IEEE TCYB), 2020, in press.
2019
- M. Ling and X. Geng, Indoor Crowd Counting by Mixture of Gaussians Label Distribution Learning. IEEE Transactions on Image Processing (IEEE TIP), 2019, 28(11): 5691-5701.
- H. Zhang, X. Geng, Y. Zhang, and F. Cheng, Recurrent age estimation. Pattern Recognition Letters (PRL), 2019, 125: 271-277.
- M. Ling and X. Geng, Soft video parsing by label distribution learning. Frontiers of Computer Science (FCS), 2019, 13(2): 302–317.
2018
- 耿新, 徐宁, 标记分布学习与标记增强, 中国科学: 信息科学, 2018, 48(5): 521-530.
- M.-L. Zhang, Y.-K. Li, X.-Y. Liu, X. Geng. Binary relevance for multi-label learning: an overview. Frontiers of Computer Science (FCS), 2018, 12(2): 191-202.
2017
- B.-B. Gao, C. Xing, C.-W. Xie, J. Wu, and X. Geng. Deep Label Distribution Learning with Label Ambiguity. IEEE Transactions on Image Processing (IEEE TIP), 2017, 26(6): 2825-2838.
- Z. He, X. Li, Z. Zhang, F. Wu, X. Geng, Y. Zhang, M.-H Yang, and Y. Zhuang. Data-Dependent Label Distribution Learning for Age Estimation, IEEE Transactions on Image Processing (IEEE TIP), 2017, 26(8): 3846-3858.
2016
- X. Geng. Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2016, 28(7): 1734-1748. [Code] [Data].
- H. Zheng and X. Geng. A Multi-Task Model for Simultaneous Face Identification and Facial Expression Recognition. Neurocomputing, 2016, vol. 171: 515-523.
2015
- Z. Zhang, M. Wang, X. Geng. Crowd Counting in Public Video Surveillance by Label Distribution Learning. Neurocomputing, 2015, vol. 166: 151-163. [Code]
Earlier
- X. Geng, C. Yin, and Z.-H. Zhou. Facial Age Estimation by Learning from Label Distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2013, 35(10): 2401-2412. [Code]
- X. Geng, K. Smith-Miles, Z.-H. Zhou, and L. Wang. Face Image Modeling by Multilinear Subspace Analysis with Missing Values. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics (IEEE TSMC-B), 2011, 41(3): 881 - 892.
- L. Wang, X. Geng, J. Bezdek, C. Leckie, K. Ramamohanarao, Enhanced Visual Analysis for Cluster Tendency Assessment and Data Partitioning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2010, 22(10): 1401-1414.
- X. Geng, K. Smith-Miles, L. Wang, M. Li, Q. Wu, Context-Aware Fusion: A Case Study on Fusion of Gait and Face for Human Identification in Video. Pattern Recognition (PRJ), 2010, 43(10): 3660-3673.
- X. Geng, Z.-H. Zhou, and K. Smith-Miles, Individual Stable Space: An Approach to Face Recognition under Uncontrolled Conditions. IEEE Transactions on Neural Networks (IEEE TNN), 2008, 19(8): 1354-1368.
- X. Geng, Z.-H. Zhou, and K. Smith-Miles. Automatic Age Estimation based on Facial Aging Patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2007, 29(12): 2234-2240.
- X. Geng, D.-C. Zhan, and Z.-H. Zhou. Supervised Nonlinear Dimensionality Reduction for Visualization and Classification. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics (IEEE TSMC-B), 2005, 35 (6): 1098-1107.
- X. Geng and Z. -H. Zhou. Image Region Selection and Ensemble for Face Recognition. Journal of Computer Science & Technology (JCST), 2006, 21(1): 116-125.
- Z.-H. Zhou and X. Geng. Projection Functions for Eye Detection. Pattern Recognition (PRJ), 2004, 37(5): 1049-1056.
Conference Papers
2022
- S.-Y. Xia, J. Lv, N. Xu, and X. Geng, Ambiguity-Induced Contrastive Learning for Instance-Dependent Partial Label Learning, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'22), Vienna, Austria, 2022, in press.
- X. Zhao, Y. An, N. Xu, and X. Geng, Fusion Label Enhancement for Multi-Label Learning, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'22), Vienna, Austria, 2022, in press.
- Q.-F. Wang, X. Geng, S.-X. Lin, S.-Y. Xia, L. Qi, N. Xu. Learngene: From Open-World to Your Learning Task. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI'22), Vancouver, Canada, 2022, in press.
2021
- N. Xu, C. Qiao, X. Geng, M.-L. Zhang, Variational Label Enhancement for Feature-Dependent Partial Label Learning (NeurIPS'21), Virtual, 2021, 1-12.
- J. Wang and X. Geng, Label Distribution Learning Machine, In: Proceedings of the International Conference on Machine Learning (ICML'21), Vienna, Austria, 2021, 10749-10759.
- J. Wang and X. Geng, Learn the Highest Label and Rest Label Description Degrees, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'21), Montreal, Canada, 2021, 3097-3103.
- Y. Gao, N. Xu, and X. Geng, Video Summarization via Label Distributions Dual-reward, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'21), Montreal, Canada, 2021, 2403-2409.
2020
- L. Feng, J. Lv, B. Han, M. Xu, G. Niu, X. Geng, B. An, and M. Sugiyama, Provably Consistent Partial-Label Learning, In: Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS'20), Vancouver, Canada, 2020, 1-13.
- N. Xu, J. Shu, Y.-P. Liu, X. Geng, Variational Label Enhancement, In: Proceedings of the International Conference on Machine Learning (ICML'20), Vienna, Austria, 2020, 10597-10606.
- J. Lv, M. Xu, L. Feng, G. Niu, X. Geng, M. Sugiyama, Progressive Identification of True Labels for Partial-Label Learning, In: Proceedings of the International Conference on Machine Learning (ICML'20), Vienna, Austria, 2020, 6500-6510.
- S. Chen, J. Wang, Y. Chen, Z. Shi, X. Geng, and Y. Rui. Label Distribution Learning on Auxiliary Label Space Graphs for Facial Expression Recognition. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’20), Seattle, WA, 2020, 13981-13990.
- Y. Gao, Y. Zhang, X. Geng, Label Enhancement for Label Distribution Learning via Prior Knowledge, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'20), Yokohama, Japan, 2020, 3223-3229.
- Y. Liu, N. Xu, Y. Zhang, X. Geng, Label Distribution for Learning with Noisy Labels, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'20), Yokohama, Japan, 2020, 2568-2574.
- N. Xu, Y.-P. Liu, X. Geng. Partial Multi-Label Learning with Label Distribution. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI'20), New York, NY, 2020, 6510-6517.
2019
- K. Su, D. Yu, Z. Xu, X. Geng and C. Wang. Multi-Person Pose Estimation with Enhanced Channel-wise and Spatial Information. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’19), Long Beach, CA, 2019, 5674-5682.
- J. Wang and X. Geng. Classification with Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'19), Macao, China, 2019, 3712-3718.
- K. Wang, X. Geng. Discrete Binary Coding based Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'19), Macao, China, 2019, 3733-3739.
- J. Lv, N. Xu, R. Zheng, X. Geng. Weakly Supervised Multi-Label Learning via label Enhancement. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'19), Macao, China, 2019, 3101-3107.
- C. Xu and X. Geng, Hierarchical Classification based on Label Distribution Learning. In: Proceedings of the 33rd AAAI C, onference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, 5533-5540.
- K. Su and X. Geng, Soft Facial Landmark Detection by Label Distribution Learning. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, 5008-5015.
- J. Wang and X. Geng, Theoretical Analysis of Label Distribution Learning. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, 5256-5263.
- N. Xu, J. Lv and X. Geng, Partial Label Learning via Label Enhancement. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, 5557-5564.
2018
- N. Xu, A. Tao and X. Geng. Label Enhancement for Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2926-2932.
- K. Wang and X. Geng. Binary Coding based Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2783-2789.
- C.-L. Peng, A. Tao and X. Geng. Label Embedding Based on Multi-Scale Locality Preservation. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2623-2629.
- Bin-Bin Gao, Hong-Yu Zhou, Jianxin Wu, and Xin Geng. Age Estimation Using Expectation of Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 712-718.
- R. Shao, N. Xu, X. Geng. Multi-label Learning with Label Enhancement. In: Proceedings of the 18th IEEE International Conference on Data Mining (ICDM'18), Singapore, 2018, 437-446.
2017
- Z. Huo and X. Geng. Ordinal Zero-Shot Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, 1331-1337.
- Y. Ren and X. Geng. Sense Beauty by Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, 2648-2654.
- X. Geng and M. Ling. Soft Video Parsing by Label Distribution Learning. In: Proceedings of the 31th AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, 2017, 1331-1337.
- P. Hou, X. Geng, Z. Huo, and J-Q Lv. Semi-supervised Adaptive Label Distribution Learning for Facial Age Estimation. In: Proceedings of the 31th AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, 2017, 2015-2021.
2016
- C. Xing, X. Geng and H. Xue. Logistic Boosting Regression for Label Distribution Learning. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’16), Las Vegas, NV, 2016, 4489-4497.
- X. Yang, X. Geng and D.-Y. Zhou. Sparsity Conditional Energy Label Distribution Learning for Age Estimation. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'16), New York City, NY, 2016, 2259-2265.
- P. Hou, X. Geng and M.-L. Zhang. Multi-Label Manifold Learning. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, 1680-1686. [Code]
- D. Zhou, Y. Zhou, X. Zhang, Q. Zhao and X. Geng. Emotion Distribution Learning from Texts. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP'16), Austin, TX, 2016, 638-647.
2015
- Y.-K. Li, M.-L. Zhang and X. Geng. Leveraging Implicit Relative Labeling-importance Information for Effective Multi-label Learning. In: Proceedings of the 15th IEEE International Conference on Data Mining (ICDM'15), Atlantic City, NJ, 2015, 251-260. [Code]
- Y. Zhou, H. Xue and X. Geng, Emotion Distribution Recognition from Facial Expressions. In: Proceedings of the 23rd ACM International Conference on Multimedia (ACM MM'15), Brisbane, Australia, 2015, 1247-1250. [Code]
- X. Geng and P. Hou. Pre-release Prediction of Crowd Opinion on Movies by Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015, 3511-3517. [Code]
Earlier
- X. Geng and Y. Xia. Head Pose Estimation Based on Multivariate Label Distribution. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'14), Columbus, OH, 2014, pp. 1837-1842. [Code]
- X. Geng and L. Luo. Multilabel Ranking with Inconsistent Rankers. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'14), Columbus, OH, 2014, pp. 3742-3747. [Code]
- X. Geng, Q. Wang, and Y. Xia. Facial Age Estimation by Adaptive Label Distribution Learning. In: Proceedings of the 22nd International Conference on Pattern Recognition (ICPR'14, Oral), Stockholm, Sweden, 2014, pp. 4465-4470. [Code]
- X. Geng, K. Smith-Miles, Z.-H. Zhou. Facial Age Estimation by Learning from Label Distributions. In: Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI'10), Atlanta, GA, 2010, pp. 451-456. [Code]
- X. Geng, K. Smith-Miles, Z.-H. Zhou, and L. Wang. Face Image Modeling by Multilinear Subspace Analysis with Missing Values. In: Proceedings of the 17th ACM International Conference on Multimedia (ACM MM'09), Beijing, China, 2009, pp. 629-632.
- X. Geng and K. Smith-Miles. Facial Age Estimation by Multilinear Subspace Analysis. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'09), Taipei, Taiwan, 2009, pp. 865-868.
- X. Geng, K. Smith-Miles, and Z.-H. Zhou. Facial Age Estimation by Nonlinear Aging Pattern Subspace. In: Proceedings of the 16th ACM International Conference on Multimedia (ACM MM'08), Vancouver, Canada, 2008, pp. 721-724.
- L. Wang, X. Geng, C. Leckie, R. Kotagiri, Moving Shape Dynamics: A Signal Processing Perspective. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'08), Anchorage, AK, 2008, pp. 1-8.
- L. Wang, X. Geng, J. Bezdek, C. Leckie, and R. Kotagiri, SpecVAT: Enhanced Visual Cluster Analysis. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), Pisa, Italy, 2008, pp. 638-647.
- X. Geng, L. Wang, M. Li, Q. Wu, and K. Smith-Miles. Adaptive Fusion of Gait and Face for Human Identification in Video. In: Proceedings of IEEE 2008 Workshop on Application of Computer Vision (WACV'08), Copper Mountain Resort, CO, 2008, pp. 1-6.
- X. Geng, Z.-H. Zhou, Y. Zhang, G. Li, and H. Dai. Learning from Ffacial Aging Patterns for Automatic Age Estimation. In: Proceedings of the 14th ACM International Conference on Multimedia (ACM MM'06), Santa Barbara, CA, 2006, pp. 307-316.
- X. Geng, Z.-H. Zhou, and H. Dai. Uncontrolled Face Recognition by Individual Stable Neural Network. In: Proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence (PRICAI'06), Guilin, China, LNAI 4099, 2006, pp. 553-562.
Book
- L. Wang and X. Geng eds. Behavioral Biometrics for Human Identification: Intelligent Applications, IGI Global, Hershey PA, USA, 2009.
Book Chapters
- X. Geng, Facial Age Estimation: A Data Representation Perspective. Yun Fu ed., Human-Centered Social Media Analytics, Springer, NY, USA, 2014.
- X. Geng and K. Smith-Miles, Incremental Learning. Stan Z. Li ed., Encyclopedia of Biometrics, Springer, NY, USA, 2009.
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Courses
- Fundamentals of Data Structure (for undergraduate students)
- Pattern Recognition (for undergraduate students)
- Pattern Recognition (for graduate students)
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Codes & Data
My research interests include machine learning, pattern recognition, and computer vision.
Most of my recent focus is on Label Distribution Learning (LDL). Label Distribution Learning is a novel machine learning paradigm. A label distribution covers a certain number of labels, representing the degree to which each label describes the instance. LDL is a general learning framework which includes both single-label and multi-label learning as its special cases.
The right is the top-100 word cloud generated from my recent published papers.