Correspondence

Mail: School of Computer Science and Engineering,
Jiulonghu Campus, Southeast University,
Nanjing 211189, China
Office: 516, Computer Science Building,
Jiulonghu Campus, Southeast University
Nanjing 211189, China
Email: xgeng AT seu.edu.cn

Research Interests | Selected Publication | Courses | Codes & Data

Research Interests

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.

For future students（2025级硕士/博士研究生报名）

Research Interest

Selected Publications

Journal Papers

    2024
  1. Yongbiao Gao, Sijie Niu, Guohua Lv, Miaogen Ling, and Xin Geng. Long and Recent Preference Learning with Recent-k Items Distribution for Recommender System. Transactions on Multimedia (TMM), 2024, in press.
  2. Huazhong Zhao, Lei Qi, and Xin Geng. CLIP-DFGS: A Hard Sample Mining Method for CLIP in Generalizable Person Re-Identification. ACM Transactions on Multimedia Computing Communications and Applications (TOMM), 2024, in press.
  3. Xingyu Zhao, Yuexuan An, Lei Qi, and Xin Geng. Scalable Label Distribution Learning for Multi-Label Classification. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024, in press.
  4. Lei Qi, Dongjia Zhao, Yinghuan Shi, and Xin Geng. Patch-aware Batch Normalization for Improving Cross-domain Robustness. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024, in press.
  5. Shunxin Guo, Hongsong Wang, Shuxia Lin, Zhiqiang Kou, and Xin Geng. Addressing Skewed Heterogeneity via Federated Prototype Rectification with Personalization. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024, in press.
  6. Jing Wang, Zhiqiang Kou, Yuheng Jia, Jianhui Lv, and Xin Geng. Label Distribution Learning by Exploiting Fuzzy Label Correlation. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024, in press.
  7. Yunlong Tang, Yuxuan Wan, Lei Qi, and Xin Geng. DPStyler: Dynamic PromptStyler for Source-Free Domain Generalization. Transactions on Multimedia (TMM), 2024, in press.
  8. Shunxin Guo, Hongsong Wang, and Xin Geng. Dynamic heterogeneous federated learning with multi-level prototypes. Pattern Recognition (PRJ), 2024, 153: 110542.
  9. Yuexuan An, Hui Xue, Xingyu Zhao, Ning Xu, Pengfei Fang, and Xin Geng. Leveraging Bilateral Correlations for Multi-Label Few-Shot Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024, in press.
  10. Dongjia Zhao, Lei Qi, Xiao Shi, Yinghuan Shi, and Xin Geng. A Novel Cross-Perturbation for Single Domain Generalization. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024, in press.
  11. Lei Qi, Ziang Liu, Yinghuan Shi, and Xin Geng. Generalizable Metric Network for Cross-domain Person Reidentification. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024, in press.
  12. Zhiqiang Kou, Jing Wang, Yuheng Jia, and Xin Geng. Inaccurate Label Distribution Learning. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024, 34(10): 10237-10249.
  13. Xiangyi Li, Jiajia Guo, Chao-Kai Wen, Xin Geng, and Shi Jin. Facilitating AI-based CSI Feedback Deployment in Massive MIMO Systems with Learngene. IEEE Transactions on Wireless Communications (TWC), 2024, 23(9): 11325-11340.
  14. Hao Gu, Jian Gu, Keyu Peng, Ziran Zhu, Ning Xu, Xin Geng, and Jun Yang. LAMPlace: Legalization-Aided Reinforcement Learning Based Macro Placement for Mixed-Size Designs With Preplaced Blocks. IEEE Transactions on Circuits and Systems II: Express Briefs (TCAS-II), 2024, 71(8): 3770-3774.
  15. Lei Qi, Hongpeng Yang, Yinghua Shi, and Xin Geng. MultiMatch: Multi-task Learning for Semi-supervised Domain Generalization. ACM Transactions on Multimedia Computing Communications and Applications (TOMM), 2024, 20(6): 184:1-184:21.
  16. Jin Yuan, Feng Hou, Ying Yang, Yang Zhang, Zhongchao Shi, Xin Geng, Jianping Fan, Zhiqiang He, and Yong Rui. Domain-Aware Graph Network for Bridging Multi-Source Domain Adaptation. Transactions on Multimedia (TMM), 2024, 7210-7224.
  17. Lei Qi, Hongpeng Yang, Yinghuan Shi, and Xin Geng, NormAUG: Normalization-guided Augmentation for Domain Generalization. IEEE Transactions on Image Processing (IEEE TIP), 2024, 26: 7210-7224.
  18. Jing Wang and Xin Geng. Explaining the Better Generalization of Label Distribution Learning for Classification. SCIENCE CHINA Information Sciences (SCIS), 2024, in press.

    19. 2023
  19. Lei Qi, Peng Dong, Tan Xiong, Hui Xue, and Xin Geng. DoubleAUG: Single-Domain Generalized Object Detector in Urban via Color Perturbation and Dual-style Memory. ACM Transactions on Multimedia Computing Communications and Applications (TOMM), 2023, 20(5): 126:1-126:20.
  20. Xingyu Zhao, Yuexuan An, Ning Xu, and Xin Geng. Variational Continuous Label Distribution Learning for Multi-Label Text Classification. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 36(6): 2716-2729.
  21. Hao Yang, You-Zhi Jin, Zi-Yin Li, Deng-Bao Wang, Xin Geng, and Min-Ling Zhang. Learning From Noisy Labels via Dynamic Loss Thresholding. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 36(11): 6503-6516.
  22. Jing Wang and Xin Geng. Large Margin Weighted k-Nearest Neighbors Label Distribution Learning for Classification. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, 35(11): 16720-16732.
  23. Jing Wang, Jianhui Lv and Xin Geng. Label Distribution Learning by Partitioning Label Distribution Manifold. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, in press.
  24. Yu Zhang, Junjie Zhao, Zhengjie Chen, Siya Mi, Hongyuan Zhu, and Xin Geng. A Closer Look at Video Sampling for Sequential Action Recognition. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023, 33(12): 7503-7514.
  25. Yu Zhang, Zhengjie Chen, Tianyu Xu, Junjie Zhao, Siya Mi, Xin Geng, and Min-Ling Zhang. Temporal Segment Dropout for Human Action Video Recognition. Pattern Recognition (PRJ), 2023, 146: 109985.
  26. Miaogen Ling, Tianhang Pan, Yi Ren, Ke Wang, and Xin Geng. Motional Foreground Attention-Based Video Crowd Counting. Pattern Recognition (PRJ), 2023, 144: 109891.
  27. Lei Qi, Jiaqi Liu, Lei Wang, Yinghuan Shi, and Xin Geng. Unsupervised Generalizable Multi-source Person Re-identification: A Domain-specific Adaptive Framework. Pattern Recognition (PRJ), 2023, 140: 109546.
  28. Ning Xu, Yong-Di Wu, Congyu Qiao, Yi Ren, Minxue Zhang, and Xin Geng. Multi-View Partial Multi-Label Learning via Graph-Fusion-Based Label Enhancement. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 35(11): 11656-11667.
  29. Jin Yuan, Shikai Chen, Yao Zhang, Zhongchao Shi, Xin Geng, Jianping Fan, and Yong Rui. Graph Attention Transformer Network for Multi-Label Image Classification. ACM Transactions on Multimedia Computing Communications and Applications (TOMM), 2023, 19(4): 150:1-150:16.
  30. Tiankai Hang, Huan Yang, Bei Liu, Jianlong Fu, Xin Geng, and Baining Guo. Language-Guided Face Animation by Recurrent StyleGANbased Generator. Transactions on Multimedia (TMM), 2023, in press.
  31. Boyu Zhang, Jiayuan Chen, Yinfei Xu, Hui Zhang, Xu Yang, and Xin Geng. Auto-Encoding score distribution regression for action quality assessment. Neural Computing and Applications, 2023, 36(2): 929-942.
  32. Adam A. Q. Mohammed, Xin Geng, Jing Wang, and Zafar Ali. Driver Distraction Detection Using Semi-Supervised Lightweight Vision Transformer. Engineering Applications of Artificial Intelligence, 2023, 129: 107618.
  33. Zihan Chen, Hongyuan Zhu, Hao Cheng, Siya Mi, Yu Zhang, and Xin Geng. LPCL: Localized Prominence Contrastive Learning for Self-Supervised Dense Visual Pre-Training. Pattern Recognition (PRJ), 2023, 135: 109185.
  34. Chao Tan, Sheng Chen, Xin Geng, and Genlin Ji. A Novel Label Enhancement Algorithm Based on Manifold Learning. Pattern Recognition (PRJ), 2023, 135: 109189.
  35. Ning Xu, Jun Shu, Renyi Zheng, Xin Geng, Deyu Meng, and Min-Ling Zhang. Variational Label Enhancement. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2023, 45(5): 6537 - 6551.

    36. 2022
  36. Xin Geng, Renyi Zheng, Jiaqi Lv, and Yu Zhang. Multilabel Ranking with Inconsistent Rankers. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2022, 44(9): 5211-5224.
  37. Xin Geng, Xin Qian, Zengwei Huo, and Yu Zhang. Head Pose Estimation Based on Multivariate Label Distribution. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2022, 44(4): 1974-1991.
  38. Jing Wang, Xin Geng and Hui Xue. Re-weighting Large Margin Label Distribution Learning for Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2022, 44(9): 5445-5459.
  39. Kate Smith-Miles, and Xin 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.
  40. Xingyu Zhao, Yuexuan An, Ning Xu, and Xin Geng. Continuous Label Distribution Learning. Pattern Recognition (PRJ), 2022, 36(6): 2716-2729.
  41. Lei Qi, Lei Wang, Yinghuan Shi, and Xin Geng. A Novel Mix-normalization Method for Generalizable Multi-source Person Re-identification. IEEE Transactions on Multimedia (IEEE TMM), 2022, 25: 4856-4867.
  42. Ning Xu, Jiayu Li, Yun-Peng Liu, and Xin Geng. Trusted-Data-Guided Label Enhancement on Noisy Labels. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2022, 34(12): 9940-9951.
  43. Yongbiao Gao, Ke Wang, and Xin Geng. Sequential Label Enhancement. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2022, 35(5): 7204-7215.
  44. Lei Qi, Jiaying Shen, Jiaqi Liu, Yinghuan Shi, and Xin Geng. Label Distribution Learning for Generalizable Multi-source Person Re-identification. IEEE Transactions on Information Forensics & Security (TIFS), 2022, in press.
  45. Lei Qi, Lei Wang, Jing Huo, Yinghuan Shi, Xin Geng, and Yang Gao. Adversarial Camera Alignment Network for Unsupervised Cross-camera Person Re-identification. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022, 32(5): 2921-2936.
  46. Chao Tan, Sheng Chen, Genlin Ji, and Xin Geng. Multilabel Distribution Learning Based on Multioutput Regression and Manifold Learning. IEEE Transactions on Cybernetics (IEEE TCYB), 2022, 52(6): 5064-5078.
  47. Yi Ren, Ning Xu, Miaogen Ling, and Xin Geng. Label Distribution for Multimodal Machine Learning. Frontiers of Computer Science (FCS), 2022, 16: 161306.
  48. Jin Yuan, Yao Zhang, Zhongchao Shi, Xin Geng, Jianping Fan, and Yong Rui. Balanced Masking Strategy for Multi-Label Image Classification. Neurocomputing, 2022, 522: 64-72.
  49. Minxue Zhang, Ning Xu, and Xin Geng. Feature-Induced Label Distribution for Learning with Noisy Labels. Pattern Recognition Letters (PRL), 2022, 155: 107-113.
  50. Jingyang Zhou, Guangzhao Wen, Yu Zhang, and Xin Geng. Multistage Attention Network for Human Pose Estimation. J. Electron. Imaging, 2022, 31(6): 063001.

    51. Previous
  51. Ke Wang, Ning Xu, Miaogen Ling, and Xin Geng. Fast Label Enhancement for Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, 35(2): 1502-1514.
  52. Ning Xu, Yun-Peng Liu, and Xin Geng. Label Enhancement for Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, 33(4): 1632-1643.
  53. Chao Tan, Sheng Chen, Genlin Ji, and Xin Geng. A Novel Probabilistic Label Enhancement Algorithm for Multi-label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, 34(11): 5098-5113.
  54. Min-Ling Zhang, Qian-Wen Zhang, Jun-Peng Fang, Yu-Kun Li, and Xin Geng. Leveraging Implicit Relative Labeling-Importance Information for Effective Multi-Label Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, 33(5): 2057-2070.
  55. Ning Xu, Yun-Peng Liu, Yan Zhang, and Xin Geng. Progressive Enhancement of Label Distributions for Partial Multi-Label Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, 34(8): 4856-4867.
  56. Jing Wang and Xin Geng. Label Distribution Learning by Exploiting Label Distribution Manifold. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2021, 34(2): 839-852.
  57. Jiaqi Lv, Tianran Wu, Chenglun Peng, Yunpeng Liu, Ning Xu, and Xin Geng. Compact Learning for Multi-Label Classification. Pattern Recognition (PRJ), 2021, 113: 107833.
  58. Huiying Zhang, Yu Zhang, and Xin Geng. Practical Age Estimation Using Deep Label Distribution Learning. Frontiers of Computer Science (FCS), 2021, 15(3): 153318.
  59. Miaogen Ling and Xin Geng. Indoor Crowd Counting by Mixture of Gaussians Label Distribution Learning. IEEE Transactions on Image Processing (IEEE TIP), 2019, 28(11): 5691-5701.
  60. Huiying Zhang, Xin Geng, Yu Zhang, and Fanyong Cheng. Recurrent Age Estimation. Pattern Recognition Letters (PRL), 2019, 125: 271-277.
  61. Miaogen Ling and Xin Geng. Soft video parsing by label distribution learning. Frontiers of Computer Science (FCS), 2019, 13(2): 302–317.
  62. 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.
  63. Min-Ling Zhang, Yu-Kun Li, Xu-Ying Liu, and Xin Geng. Binary Relevance for Multi-Label Learning: An Overview[J]. Frontiers of Computer Science (FCS), 2018, 12(2): 191-202.
  64. 耿新, 徐宁,邵瑞枫, 面向标记分布学习的标记增强. 计算机研究与发展, 2017, 54(6): 1171-1184. EI(20173804190920)
  65. Bin-Bin Gao, Chao Xing, Chen-Wei Xie, Jianxin Wu, and Xin Geng. Deep Label Distribution Learning with Label Ambiguity. IEEE Transactions on Image Processing (IEEE TIP), 2017, 26(6): 2825 - 2838. EI(20171903647267)
  66. Zhouzhou He, Xi Li, Zhongfei Zhang, Fei Wu, Xin Geng, Yaqing Zhang, Ming-Hsuan Yang, and Yueting Zhuang. Data-Dependent Label Distribution Learning for Age Estimation, IEEE Transactions on Image Processing (IEEE TIP), 2017, 26(8): 3846 - 3858.
  67. Hao Zheng, and Xin Geng. Facial Expression Recognition via Weighted Group Sparsity. Frontiers of Computer Science (FCS), 2017, 11(2): 266-275. SCI(000399006800008)EI(20171203473958)
  68. Xin Geng. Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2016, 28(7): 1734-1748. EI(20162702559957)
  69. Hao Zheng and Xin Geng. A Multi-Task Model for Simultaneous Face Identification and Facial Expression Recognition. Neurocomputing, 2016, vol. 171: 515-523. SCI(000364883900054) EI(20153301179658)
  70. Zhaoxiang Zhang, Mo Wang, and Xin Geng. Crowd Counting in Public Video Surveillance by Label Distribution Learning. Neurocomputing, 2015, vol. 166: 151-163. SCI(000357751200016) EI(20151900835890)
  71. Xin Geng, Chao Yin, and Zhi-Hua Zhou. Facial Age Estimation by Learning from Label Distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2013, 35(10): 2401-2412. SCI(000323175200007) EI(20133616697653)
  72. 方尔庆,耿新.基于视听信息的自动年龄估计方法.软件学报,2011,22(7):1503-1523 EI (20113114199487)
  73. Xin Geng, Kate Smith-Miles, Zhi-Hua Zhou, and Liang 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. SCI(000290734400023) EI(20112214010924)
  74. Xin Geng, Kate Smith-Miles, Liang Wang, Ming Li, and Qiang 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. SCI(000280006700040) EI（20102513019416）
  75. Liang Wang, Xin Geng, James Bezdek, Christopher Leckie, and Kotagiri Ramamohanarao. Enhanced Visual Analysis for Cluster Tendency Assessment and Data Partitioning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2010, 22(10): 1401-1414. SCI(000281000500005) EI(20103513198653)
  76. Liang Wang, Qiang Wu, Hanzi Wang, Xin Geng, and Ming Li. Image/Video-Based Pattern Analysis and HCI Applications. Pattern Recognition Letters (PRL), 2009, 30(12): 1047. (rank: 40/94) SCI(000268866700001) EI(20092912201496)
  77. Liang Wang, Qiang Wu, Ming Li, Jordi Gonzalez, and Xin Geng. Video Analysis and Understanding for Surveillance Applications. International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), 2009, 23(7): 1221-1222. SCI(000271863500001) EI(20094812519078)
  78. Xin Geng, Zhi-Hua Zhou, and Kate 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. (rank: 4/94, 3/84, 10/229, 2/45) SCI(000258505700004) EI(20083411475708)
  79. Xin Geng, Zhi-Hua Zhou, and Kate 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. (“Featured Article” of the December issue) (rank: 1/94) SCI(000251580300015) EI(20074710938938)
  80. Xin Geng, De-Chuan Zhan, and Zhi-Hua 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. (rank: 8/53, 2/17, 21/94) SCI(000233441800002) EI(2005519608280)
  81. Zhi-Hua Zhou and Xin Geng. Projection Functions for Eye Detection. Pattern Recognition (PRJ), 2004, 37(5): 1049-1056. (rank: 10/94, 17/229) SCI(000220677200015) EI(2004188136937)
  82. Xin Geng and Zhi-Hua Zhou. Image Region Selection and Ensemble for Face Recognition. Journal of Computer Science & Technology (JCST), 2006, 21(1): 116-125. SCI(000235342400013) EI(2006079699543)
  83. Xin Geng, Zhi-Hua Zhou, and Shi-Fu Chen. Eye Location Based on Hybrid Projection Function (in Chinese). Journal of Software, 2003, 14(8): 1394-1400. EI(7738079)
  84. Xin Geng, Zhao-Qian Chen, and Zhi-Hua Zhou. Survey on Spatial Data Mining (in Chinese). Computer Science, 2002, 29: 341-345.

Conference Papers

    2024
  1. Shuxia Lin, Miaosen Zhang, Ruiming Chen, Xu Yang, Qiufeng Wang, and Xin Geng. Linearly Decomposing and Recomposing Vision Transformers for Diverse-Scale Models. In: Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS'24), 2024, in press.
  2. Qiufeng Wang, Xu Yang, Fu Feng, Jing wang, and Xin Geng. Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers. In: Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS'24), 2024, in press.
  3. Miaosen Zhang, Yixuan Wei, Zhen Xing, Yifei Ma, Zuxuan Wu, Ji Li, Zheng Zhang, Qi Dai, Chong Luo, Xin Geng, and Baining Guo. Aligning Vision Models with Human Aesthetics in Retrieval: Benchmarks and Algorithms. In: Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS'24), 2024, in press.
  4. Shi-Yu Xia, Xu Yang, Yuankun Zu, and Xin Geng. Initializing Variable-sized Vision Transformers from Learngene with Learnable Transformations. In: Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS'24), 2024, in press.
  5. Yingzhe Peng, chenduo hao, Xu Yang, Jiawei Peng, Xinting Hu, and Xin Geng. Learnable In-Context Vector for Visual Question Answering. In: Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS'24), 2024, in press.
  6. Jiaqi Lv, Yangfan Liu, Shiyu Xia, Ning Xu, Miao Xu, Gang Niu, Min-Ling Zhang, Masashi Sugiyama, and Xin Geng. What Makes Partial-Label Learning Algorithms Effective? In: Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS'24), 2024, in press.
  7. Biao Liu, Ning Xu, Xiangyu Fang, and Xin Geng. Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, in press.
  8. Ning Xu, Yihao Hu, Congyu Qiao, and Xin Geng. Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning. In: Proceedings of the International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, in press.
  9. Qiufeng Wang, Xu Yang, Haokun Chen, and Xin Geng. Vision Transformers as Probabilistic Expansion from Learngene. In: Proceedings of the International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, in press.
  10. Yangfan Liu, Jiaqi Lv, Xin Geng, and Ning Xu. Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency. In: Proceedings of the International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, in press.
  11. Congyu Qiao, Ning Xu, Yihao Hu, and Xin Geng. ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision. In: Proceedings of the International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, in press.
  12. Shi-Yu Xia, Wenxuan Zhu, Xu Yang, and Xin Geng. Exploring Learngene via Stage-wise Weight Sharing for Initializing Variable-sized Models. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'24), Jeju, South Korea, 2024, 5254-5262.
  13. Zhiqiang Kou, Jing Wang, Jiawei Tang, Yuheng Jia, Boyu Shi, and Xin Geng. Exploiting Multi-Label Correlation in Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'24), Jeju, South Korea, 2024, 4326-4334.
  14. Boyu Shi, Shi-Yu Xia, Xu Yang, Haokun Chen, Zhiqiang Kou, and Xin Geng. Building Variable-sized Models via Learngene Pool. In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), Vancouver, Canada, 2024, 14946-14954.
  15. Shi-Yu Xia, Miaosen Zhang, Xu Yang, Ruiming Chen, Haokun Chen, and Xin Geng. Transformer as Linear Expansion of Learngene. In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), Vancouver, Canada, 2024, 16014-16022.
  16. Yu Zhang, Jingwei Sun, Li Feng, Cen Yao, Mingming Fan, Liuxin Zhang, Qianying Wang, Xin Geng, and Yong Rui. See Widely, Think Wisely: Toward Designing Generative Multi-agents to Burst Filter Bubbles. In: The ACM CHI conference on Human Factors in Computing Systems (CHI'24), Honolulu, HI, 2024, in press.

    17. 2023
  17. Jialiang Zhu, Danqing Huang, Chunyu Wang, Mingxi Cheng, Ji Li, Han Hu, Xin Geng and Baining Guo. Adaptive Fusion of Gait and Face for Human Identification in Video. In: Proceedings of IEEE 2023 Workshop on Application of Computer Vision (WACV'24), Waikoloa, HI, 2024, 1-6.
  18. Hua Yuan, Yu Shi, Ning Xu, Xu Yang, Xin Geng, and Yong Rui. Learning From Biased Soft Labels, In: Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS'23), 2023, in press.
  19. Xu Yang, Yongliang Wu, Mingzhuo Yang, Haokun Chen, and Xin Geng. Exploring Diverse In-Context Configurations for Image Captioning, In: Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS'23), 2023, in press.
  20. Ning Xu, Biao Liu, Jiaqi Lv, Congyu Qiao, and Xin Geng. Progressive Purification for Instance-Dependent Partial Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'23), Honolulu, Hawaii, 2023, 38551-38565.
  21. Congyu Qiao, Ning Xu, Jiaqi Lv, yi Ren, and Xin Geng. FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'23), Honolulu, Hawaii, 2023, 28321-28336.
  22. Biao Liu, Ning Xu, Jiaqi Lv, and Xin Geng. Revisiting Pseudo-Label for Single-Positive Multi-Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'23), Honolulu, Hawaii, 2023, 22249-22265.
  23. Yu Shi, Ning Xu, Hua Yuan, and Xin Geng. Unreliable Partial Label Learning with Recursive Separation. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'23), Macao, China, 2023, 4208-4216.
  24. Shi-Yu Xia, Jiaqi Lv, Ning Xu, Gang Niu, and Xin Geng. Towards Effective Visual Representations for Partial-Label Learning. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’23), Vancouver, Canada, 2023, 15589-15598.
  25. Tiankai Hang, Shuyang Gu, Chen Li, Jianmin Bao, Dong Chen, Han Hu, Xin Geng, and Baining Guo. Efficient Diffusion Training via Min-SNR Weighting Strategy. In: Proceedings of the International Conference on Computer Vision (ICCV'23), Paris, France, 2023, 7407-7417.
  26. Congyu Qiao, Ning Xu, and Xin Geng. Decompositional Generation Process for Instance-Dependent Partial Label Learning. In: Proceedings of the 11th International Conference on Learning Representations (ICLR'23), Kigali, Rwanda, 2023, in press.
  27. Xingyu Zhao，Yuexuan An，Ning Xu，Jing Wang，and Xin Geng. Imbalanced Label Distribution Learning. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI'23), Washington, DC, 2023, 11336-11344.

    28. 2022
  28. Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, and Min-Ling Zhang. One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement, In: Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS'22), 2022, in press.
  29. Jin Yuan, Feng Hou, Yangzhou Du, Zhongchao Shi, Xin Geng, Jianping Fan, and Yong Rui. Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation. In: Proceedings of the 30th ACM International Conference on Multimedia (ACM MM'22), Lisbon, Portugal, 2022, 3907-3916.
  30. Ziyang Gao, Yaping Yan, and Xin Geng. Learning from Noisy Labels via Meta Credible Label Elicitation. In: Proceedings of the IEEE International Conference on Image Processing (ICIP'22), Bordeaux, France, 2022, 1391-1395.
  31. Shi-Yu Xia, Jiaqi Lv, Ning Xu, and Xin 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, 3615-3621.
  32. Xingyu Zhao, Yuexuan An, Ning Xu, and Xin Geng. Fusion Label Enhancement for Multi-Label Learning, In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'22), Vienna, Austria, 2022, 3773-3779.
  33. Qiu-Feng Wang, Xin Geng, Shu-Xia Lin, Shi-Yu Xia, Lei Qi, and Ning Xu. Learngene: From Open-World to Your Learning Task. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI'22), Vancouver, Canada, 2022, 8557-8565.

    34. Previous
  34. Ning Xu, Congyu Qiao, Xin Geng, and Min-Ling Zhang. Instance-Dependent Partial Label Learning. In: Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS'21), Sydney, Australia, 2021, 1-12.
  35. Jing Wang and Xin Geng. Label Distribution Learning Machine. In: Proceedings of the International Conference on Machine Learning (ICML'21), Vienna, Austria, 2021, PMLR 139: 10749-10759.
  36. Jing Wang and Xin 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.
  37. Yongbiao Gao, Ning Xu, and Xin 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.
  38. Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, and Masashi Sugiyama. Provably Consistent Partial-Label Learning. In: Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS'20), Vancouver, Canada, 2020, 1-13.
  39. Ning Xu, Jun Shu, Yun-Peng Liu, and Xin Geng. Variational Label Enhancement. In: Proceedings of the International Conference on Machine Learning (ICML'20), Vienna, Austria, 2020, PMLR 119: 10597-10606.
  40. Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, and Masashi Sugiyama. Progressive Identification of True Labels for Partial-Label Learning. In: Proceedings of the International Conference on Machine Learning (ICML'20), Vienna, Austria, 2020, PMLR 119:6500-6510.
  41. Yongbiao Gao, Yu Zhang, and Xin 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.
  42. Yunpeng Liu, Ning Xu, Yu Zhang, and Xin 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.
  43. ShiKai Chen, Jianfeng Wang, Yuedong Chen, Zhongchao Shi, Xin Geng, and Yong 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.
  44. Ning Xu, Yun-Peng Liu, and Xin 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.
  45. Kai Su, Dongdong Yu, Zhenqi Xu, Xin Geng, and Changhu 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.
  46. Jing Wang, and Xin Geng. Classification with Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'19), Macao, China, 2019, 3712-3718.
  47. Ke Wang, and Xin 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.
  48. Jiaqi Lv, Ning Xu, Ren-Yi Zheng, and Xin 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.
  49. Changdong Xu and Xin Geng. Hierarchical Classification Based on Label Distribution Learning. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, 5533-5540.
  50. Kai Su and Xin 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.
  51. JingWang and Xin Geng. Theoretical Analysis of Label Distribution Learning. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, 5256-5263.
  52. Ning Xu, Jiaqi Lv, and Xin Geng. Partial Label Learning via Label Enhancement. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019, 5557-5564.
  53. Ning Xu, An Tao, and Xin Geng. Label Enhancement for Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2926-2932.
  54. Ke Wang and Xin Geng. Binary Coding based Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, 2783-2789.
  55. Cheng-Lun Peng, An Tao, and Xin 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.
  56. 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.
  57. Ruifeng Shao, Ning Xu, and Xin Geng. Multi-label Learning with Label Enhancement. In: Proceedings of the 18th IEEE International Conference on Data Mining (ICDM'18), Singapore, 2018, 437-446.
  58. Zengwei Huo and Xin Geng. Ordinal Zero-Shot Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, 1916-1922. EI(20174304308808)
  59. Yi Ren and Xin Geng. Sense Beauty by Label Distribution Learning. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, 2648-2654. EI(20174304308761)
  60. Xin Geng and Miaogen Ling. Soft Video Parsing by Label Distribution Learning. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, 2017, 1331-1337. EI(20174104243011)
  61. Peng Hou, Xin Geng, Zeng-Wei Huo, and Jiaqi 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. EI(20174104242999)
  62. Deyu Zhou, Xuan Zhang, Yin Zhou, Quan Zhao, and Xin 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.
  63. Xu Yang, Xin Geng, and De-Yu 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. EI(20165103146988)
  64. Chao Xing, Xin Geng, and Hui 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. EI(20170403274722)
  65. Peng Hou, Xin Geng, and Min-Ling Zhang. Multi-Label Manifold Learning. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI’16), Phoenix, AZ, 2016, 1680-1686. EI(20165203195707)
  66. Hao Zheng, Xin Geng, and Zhongxue Yang. A Relaxed K-SVD Algorithm for Spontaneous Micro-Expression Recognition. In: Proceedings of the 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI'16), Phuket, Thailand, 2016, pp. 692-699. EI(20163602776534)
  67. Zeng-Wei Huo, Xu Yang, Chao Xing, Ying Zhou, Peng Hou, Jiaqi Lv, and Xin Geng. Deep Age Distribution Learning for Apparent Age Estimation. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW’16), Las Vegas, NV, 2016, 722-729.
  68. Yu-Kun Li, Min-Ling Zhang, and Xin 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. EI(20161602272585)
  69. Ying Zhou, Hui Xue, and Xin 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. EI(20161602252578)
  70. Xin Geng and Peng 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. EI(20155101693823)
  71. Xu Yang, Bin-Bin Gao, Chao Xing, Zeng-Wei Huo, Xiu-Shen Wei, Ying Zhou, Jianxin Wu, and Xin Geng. Deep Label Distribution Learning for Apparent Age Estimation. In: Proceedings of the International Conference on Computer Vision Workshops (ICCVW’15), Santiago de Chile, 2015, 344-350. EI(20161402196430)
  72. Xin Geng and Yu 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. EI(201448247522)
  73. Xin Geng and Longrun 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. EI(201448247612)
  74. Xin Geng, Qin Wang, and Yu 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. EI(20150100390700)
  75. Xin Geng and Rongzi Ji. Label Distribution Learning. In: Proceedings of the 2013 International Conference on Data Mining Workshops (ICDMW’13), Dallas, TA, 2013, pp. 377-383. EI(20141617588760)
  76. Yu Xia, Yongzhen Huang, Liang Wang, and Xin Geng. Pedestrian Detection Based on Incremental Learning. In: Proceedings of the 2013 International Conference on Intelligence Science and Big Data Engineering (IScIDE’13), Beijing, China, 2013, pp. 603-610. EI(20140517246445)
  77. Chao Yin, and Xin Geng. Facial Age Estimation by Conditional Probability Neural Network. In: Proceedings of the Chinese Conference on Pattern Recognition (CCPR’12), Beijing, China, 2012, pp. 243-250. EI(20124115549388) ISTP(000312434700031)
  78. Xin Geng, Kate Smith-Miles, and Zhi-Hua 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.(A) EI(20104413339490)
  79. Xin Geng, Kate Smith-Miles, and Zhi-Hua Zhou. Liang 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.(A) EI(20095312583466)
  80. Xin Geng and Kate 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. ISTP(000268919200217) EI(20093912338417)
  81. Liang Wang, Xin Geng, James Bezdek, Christopher Leckie, and Ramamohanarao 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. (A) ISTP(000264173600065) EI(10478558)
  82. Xin Geng, Kate Smith-Miles, and Zhi-Hua 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. (A) EI(20094612442141)
  83. Liang Wang, Xin Geng, Christopher Leckie, and Ramamohanarao 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. (A) ISTP(000259736801043) EI(20083911592027)
  84. Xin Geng, Liang Wang, Ming Li, Qiang Wu, and Kate 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. (A) ISTP(000258906400015) EI(20083711527134)
  85. Xin Geng, Liang Wang, Ming Li, Qiang Wu, and Kate Smith-Miles. Distance-Driven Fusion of Gait and Face for Human identification in video. In: Proceedings of Image and Vision Computing New Zealand Conference (IVCNZ'07), Hamilton, New Zealand, 2007, pp. 19-24. (B)
  86. Xin Geng and Ming Li. Individual Discriminative Subspace for Face Recognition Under Uncontrolled Conditions. In: Proceedings of Image and Vision Computing New Zealand Conference (IVCNZ'07), Hamilton, New Zealand, 2007, pp. 13-18. (B)
  87. Qiang Wu, Liang Wang, Xin Geng, Ming Li, and Xin He. Dynamic Biometrics Fusion at Feature Level for Video-Based Human Recognition. In: Proceedings of Image and Vision Computing New Zealand Conference (IVCNZ'07), Hamilton, New Zealand, 2007, pp. 152-157. (B)
  88. Xin Geng, Zhi-Hua Zhou, Yu Zhang, Gang Li, and Honghua Dai. Learning from Facial 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. (A) EI(20073110714730)
  89. Xin Geng, Zhi-Hua Zhou, and Honghua 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. (B) ISTP(000240091500059) EI(20064210172124)
  90. Xin Geng, Gang Li, Yangdong Ye, Yiqing Tu, and Honghua Dai. Abnormal Behavior Detection for Early Warning of Terrorist Attack. In: Proceedings of the 19th Australian Joint Conference on Artificial Intelligence (AI 2006), Hobart, Tasmania, LNAI 4304, 2006, pp. 1002-1009. ISTP(000244891200112) EI(9307480)
  91. Xin Geng and Zhi-Hua Zhou. Face Recognition Based on Selective Ensemble of Multiple Eigenspaces (in Chinese). In: Proceedings of the International Symposium on Computer Vision, Object Tracking and Recognition, Beijing, China, August, 2004.
  92. Xin Geng, Xiang-Ping Zhong, Xin-Min Zhou, Pei Sun, and Zhi-Hua Zhou. Refining Eye Location Using VPF for Face Detection (in Chinese). In: Proceedings of the 3rd Conference of Sinobiometrics of China (Sinobiometrics'03), Xi'an, China, 2002, pp. 25-28.

Courses

1. Fundamentals of Data Structure (for undergraduate students)

2. Pattern Recognition (for undergraduate students)

3. Pattern Recognition (for graduate students)

4. 人工智能通识导论

Codes & Data