邓伟洪

邓伟洪 教授  (English version)

北京邮电大学 人工智能学院教授,博士生导师

北邮“鸿雁人才”教授,教育部青年长江学者,Elsevier中国高被引学者

研究方向:计算机视觉与模式识别、可信人工智能、情感计算、多模态学习

邮箱myname@bupt.edu.cn; myname=”whdeng”,微博邓伟洪_北邮        

学术代表作

  1. Weihong Deng, Jiani Hu, Jun Guo, Compressive Binary Patterns: Designing a Robust Binary Face Descriptor with Random-Field Eigenfilters,  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol 41, no 3, pp. 758-767, 2019.
  2. Weihong Deng, Jiani Hu, Jun Guo, Face Recognition via Collaborative Representation: Its Discriminant Nature and Superposed Representation,  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 40, no. 10, pp. 2513-2521, 2018.
  3. Weihong Deng, Jiani Hu, Jiwen Lu, Jun Guo, Transform-Invariant PCA: A Unified Approach to Fully Automatic Face Alignment, Representation, and RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 36, no. 6, pp. 1275–1284, 2014.
  4. Weihong Deng, Jiani Hu, Jun Guo, Extended SRC: Undersampled Face Recognition via Intraclass Variant DictionaryIEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 34, no. 9, pp. 1864-1870, 2012.
  5. Weihong Deng, Jiani Hu, Jun Guo, Honggang Zhang, Chuang Zhang, Comments on “Globally Maximizing, Locally Minimizing: Unsupervised Discriminant Projection with Application to Face and Palm Biometrics”IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 30. no. 8, pp. 1503–1504, 2008.

科研推荐

讲授课程

  1. 模式识别及应用(通信工程、电子信息工程、数字媒体专业本科生春季学期)主要讲授贝叶斯分类线性与逻辑回归线性分类器成分分析、分类器集成、聚类分析、神经网络等基础知识、2-3次Guest Lectures。教材:模式识别(第三版),清华大学出版社;参考讲义:Stanford-CS229
  2. 神经网络与模糊系统(全校研究生秋季学期),主要讲授线性分类和回归、成分和聚类分析、参数估计、神经元与多层感知器、常用损失函数、神经网络训练方法、深度卷积神经网络、深度学习软硬件PyTorch/Tensorflow/Caffe、循环神经网络、生成对抗网络、深度强化学习、深度迁移学习、2-3次Guest Lectures等。参考讲义:Stanford-CS229/CS231n CUHK ELEG 5040 POSTECH CSED703R
  3. Metric and Feature Learning for Biometrics,Asia Biometrics School

研究领域

计算机视觉深度学习模式识别情感计算

  • 论文:近年来以在IEEE TPAMI、IJCV、TIP、TIFS、PR、CVPR、ECCV、NIPS、AAAI、SIGIR等国际期刊和会议上发表论文100余篇,研究论文被世界著名研究机构(如Google AI、斯坦福大学、加州大学伯克利分校、剑桥大学、牛津大学等)的同行引用 近7000次,入选Elsevier“中国高被引学者”;
  • 项目:作为项目负责人主持图像识别方向的国家重点研发计划课题、4项国家自然科学基金青年/面上项目等项目20多项,与华为、中兴通讯、滴滴出行、百度、阿里巴巴、腾讯、中国移动、佳能信息技术公司等企业开展广泛的技术合作;
  • 竞赛:2019年与滴滴AI Labs合作获得WIDER FACE人脸检测数据集评测第一名,2020年CVPR 迁移小样本图像识别比赛第一名,EmotiW2020的驾驶员视线识别比赛第一名,2004年开发的人脸检测算法获得863评测最高正确检测率;2008年提出的生物启发式人脸识算法获得FRGC评测实验最高识别率;
  • 学生:指导硕士生邬仲钧获得2015年中国生物特征识别学术会议(CCBR2015)最佳论文奖,指导本科生张硕、方雨珂(北邮与Queen Mary联合培养)获得2015、2018年英国工程技术学会年度优秀学生奖,张耀斌、方瀚、江静获得年北京市优秀学士学位论文,李珊、陈炳辉获得北邮优秀博士学位论文,李珊获得博士生国家奖学金并入选“博新计划”等。
  • 服务:国际人工智能联合会议(IJCAI 2020),ACM多媒体大会(ACM MM 2021)国际多媒体大会(ICME 2020),国际模式识别会议(ICPR 2020),国际生物特征识别大会(IJCB 2021)等会议的领域主席。长期担任国家 / 北京市 / 浙江省自然科学基金项目评审专家,教育部人才计划 / 学位中心 / 科技发展中心评审专家,电子学会科技奖 / 人工智能学会吴文俊奖评审专家,IEEE Transactions on Biometrics, Behavior, and Identity Science客座编委,《中国图象图形学报》青年编委、国际期刊Image and Vision Computing客座编委,10余个高水平学术期刊(IEEE TPAMI / TIP / TNNLS / TIFS / TC / TSMC-B / TMM / THMS, IJCV, PR / PRL, IVC, 电子 / 计算机 / 自动化学报等)和主要国际会议(CVPR / ECCV / ICCV / NIPS / ICASSP / ICME / ICPR / ICB / BTAS / FG等)的审稿人。担任中国计算机学会青年计算机科技论坛(CCF YOCSEF)委员,VALSE(视觉与学习青年学者研讨会)在线委员会委员,中国计算机学会计算机视觉专委会、中国图像图形学会情感计算与理解专委会、机器视觉专委会、成像探测与感知专委会、视觉大数据专委会、人机交互专委会委会、中国自动化学会混合智能专委会、中国人工智能学会情感智能专委会委员、北京医学会数字医学分会委员。

应邀学术报告

  1. 可信人脸识别与分析,深圳大学、中山大学、武汉大学、北大科技园、山东省人工智能大会、PRCV2021讲习班
  2. Fairness Problems in Face Recognition,ICB 2021 Tutorial
  3. 视觉情感计算,VALSE 2021 
  4. 可信人脸识别的攻防与鉴伪,VALSE 2021 Workshop 
  5. 跨域人脸与表情识别,2020中国计算机大会论坛报告、华为中央媒体院、阿里达摩院、中国图象图形学报在线报告视频
  6. 人脸识别与分析中的数据偏差,2020年NCIG讲习班
  7. Uncertainty and Bias in Face Recognition and Expression Analysis, ICCV 2019 Workshopyoutube视频)、四川大学、南京理工大学、江南大学、同济大学、百度等
  8. Deep learning for visual recognition, HYU-BUPT Joint Workshop 2019 韩国汉阳大学
  9. 大规模深度人脸与表情识别,PRCV 2019讲习班
  10. 真实世界人脸表情识别研究进展,VALSE 2019、PRCV 2019专题论坛
  11. 真实世界的表情识别,VALSE 2018 Workshop、深圳大学
  12. 变换不变性主成分分析及其在人脸识别中的应用,中科院自动化所
  13. 小样本模式识别新技术,清华大学、北京交通大学
  14. 深度人脸识别与表情分析,北京大学
  15. 扩展稀疏表示及其在人脸识别中的应用,中科院计算所、西南交通大学
  16. 深度人脸识别的进展和挑战,滴滴出行AI Labs
  17. 人脸识别最新研究进展,腾讯优图
  18. 人脸分析与识别新问题与数据库,重庆大学、西北工业大学
  19. “Distance Metric Learning for Face Recognition”,2016年国际生物特征识别冬季学校,吉隆坡
  20. “Distance Metric Learning for Visual Recognition”, IEEE计算机视觉与模式识别会议CVPR2015)教学报告,美国波士顿
  21. “Discriminative Learning for Single-Sample Face Recognition”,国际人脸和姿态识别学术会议(FG2015)教学报告,斯洛文尼亚
  22. “Learning-based Feature Extraction for Social Media Analysis”,IEEE 国际多媒体技术大会(ICME2014)教学报告,成都
  23. “Metric Learning for Visual Recognition”,亚洲计算机视觉技术大会(ACCV2014)教学报告,新加坡
  24. “人脸识别中的线性模型”,中国生物特征识别会议(CCBR2014)主题报告,沈阳

主持国家级科研项目

  1. 知识产权综合服务平台及便携式监测终端研发,国家重点研发计划课题
  2. 大姿态变化条件下的深度人脸识别研究 ,国家自然科学基金面上项目
  3. 基于深度特征学习的人脸识别研究,国家自然科学基金面上项目
  4. 基于扩展稀疏表示的多姿态人脸识别研究,国家自然科学基金面上项目
  5. 基于主动感知的人脸识别研究,国家自然科学基金青年基金项目

 研究论文列表(时间倒序)

  1. Mei Wang, Yaobin Zhang, Weihong Deng, Meta Balanced Network for Fair Face Recognition, IEEE TPAMI 2021
  2. Yaoyao Zhong, Weihong Deng, et al. Dynamic Training Data Dropout for Robust Deep Face Recognition, IEEE TMM 2021
  3. Jiahao Liang, Weihong Deng, Identifying Rhythmic Patterns for Face Forgery Detection and Categorization, IJCB 2021
  4. Yaobin Zhang, Weihong Deng, et al, Adaptive Label Noise Cleaning with Meta-Supervision for Deep Face Recognition, ICCV 2021
  5. Chengrui Wang, Weihong Deng, Representative Forgery Mining for Fake Face Detection, CVPR 2021
  6. Yaoyao Zhong, Weihong Deng, et al., SFace: Sigmoid-constrained Hypersphere Loss for Robust Face Recognition, IEEE Transactions on Image Processing 2021.
  7. Mei Wang, Weihong Deng, Cycle Label-Consistent Networks for Unsupervised Domain Adaptation, Neurocomputing, 2021
  8. Mei Wang, Weihong Deng, Deep Face Recognition: A survey, Neurocomputing, 2021
  9. Yaoyao Zhong, Weihong Deng, Towards Transferable Adversarial Attack against Deep Face Recognition, IEEE Transactions on Information Forensics & Security, 2021
  10. Shanming Yang, Weihong Deng, Mei Wang, Junping Du, Jiani Hu, Orthogonality Loss: Learning Discriminative Representations for Face Recognition, IEEE Transactions on Circuits and Systems for Video Technology, 2020
  11. Shan Li, Weihong Deng, Deep Face Expression Recognition: A Survey, IEEE Transactions on Affective Computing 2020
  12. Han Fang, Weihong Deng, Yaoyao Zhong, Jiani Hu, Generate to Adapt: Resolution Adaption Network for Surveillance Face Recognition, ECCV 2020
  13. Yaobin Zhang, Weihong Deng, Class-Balanced Training for Deep Face Recognition, CVPR Workshop 2020
  14. Han Fang, Weihong Deng, Triple-GAN: Progressive Face Aging With Triple Translation Loss, CVPR Workshop 2020
  15. Yaobing Zhang, Weihong Deng, et al., Global-Local GCN: Large-Scale Label Noise Cleansing for Face Recognition, CVPR 2020
  16. Xiehe Huang, Weihong Deng, et al.,  PropagationNet: Propagate Points to Curve to Learn Structure Information, CVPR 2020
  17. Mei Wang, Weihong Deng, Mitigating Bias in Face Recognition using Skewness-Aware Reinforcement Learning, CVPR 2020
  18. Y Fang, W Deng, J Du, J Hu, Identity-aware CycleGAN for face photo-sketch synthesis and recognition, Pattern Recognition 2020
  19. S Li, W Deng, A Deeper Look at Facial Expression Dataset Bias, IEEE Transactions on Affective Computing 2020
  20. M Wang, W Deng, Deep Face Recognition with Clustering based Domain Adaptation, Neurocomputing 2020
  21. Mei Wang, Weihong Deng, et al., Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation Network, ICCV 2019.
  22. Bingyu Liu, Weihong Deng, et al., Fair Loss: Margin-aware Reinforcement Learning for Deep Face Recognition, ICCV 2019.
  23. Yaoyao Zhong, Weihong Deng, et al., Adversarial Learning with Margin-based Triplet Embedding Regularization, ICCV 2019.
  24. Binghui Chen, Weihong Deng, et al., Mixed High-Order Attention Network for Person Re-Identification, ICCV 2019.
  25. Yaoyao Zhong, Weihong Deng, Mei Wang, Jiani Hu, et al., Unequal-training for deep face recognition with long-tailed noisy data, CVPR 2019.
  26. Tongtong Yuan, Weihong Deng, Jian Tang, Jiani Hu, et al., Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning, CVPR 2019.
  27. Binghui Chen, Weihong Deng, Hybrid-Attention based Decoupled Embedding Learning for Zero-Shot Image Retrieval, CVPR 2019.
  28. Yichen Qian, Weihong Deng, Jiani Hu, Unsupervised Face Normalization with Extreme Pose and Expression in the Wild, CVPR 2019.
  29. Shan Li, Weihong Deng, Blended Emotion in-the-Wild: Multi-label Facial Expression Recognition Using Crowdsourced Annotations and Deep Locality Feature Learning, International Journal of Computer Vision (IJCV), 2019.
  30. Binghui Chen, Weihong Deng, Deep embedding learning with adaptive large margin N-pair loss for image retrieval and clustering. Pattern Recognit. 93: 353-364, 2019.
  31. Binghui Chen, Weihong Deng, Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering, AAAI, 2019.
  32. Tongtong Yuan, Weihong Deng, Jiani Hu, Zhanfu An, Yinan Tang, Unsupervised Adaptive Hashing Based on Feature Clustering, Neurocomputing, 2019
  33. Binghui Chen, Weihong Deng, Haifeng Shen, Virtual Class Enhanced Discriminative Embedding Learning, NIPS 2018 (Spotlight)
  34. Shan Li, Weihong Deng, Reliable Crowdsourcing and Deep Locality-Preserving Learning for Unconstrained Facial Expression Recognition, IEEE Transactions on Image Processing, 2018.
  35. Yida Wang, Weihong Deng, Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models, IEEE Transactions on Image Processing, 2018.
  36. Hongjun Wang, Jiani Hu, Weihong Deng, Face Feature Extraction: A Complete Review. IEEE Access 6: 6001-6039, 2018.
  37. Weihong Deng, Hongjun Wang, Face recognition with compressed Fisher vector on multiscale convolutional features. IET Biometrics 7(5): 447-453, 2018
  38. Mei Wang, Weihong Deng, Deep Visual Domain Adaptation: A Survey, Neurocomputing (2018), doi: 10.1016/j.neucom.2018.05.083
  39. Weihong Deng, Jiani Hu, Jun Guo, Compressive Binary Patterns: Designing a Robust Binary Face Descriptor with Random-Field Eigenfilters,  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),  2018.
  40. Shan Li, Weihong Deng, Deep Emotion Transfer Network for Cross-database Facial Expression Recognition, International Conference on Pattern Recognition (ICPR), 2018.
  41. Zimeng Luo, Jiani Hu, Weihong Deng, Local Subclass Constraint for Facial Expression Recognition in the Wild, International Conference on Pattern Recognition (ICPR), 2018.
  42. Yaoyao Zhong, Weihong Deng, Deep Difference Analysis in Similar-looking Face recognition, International Conference on Pattern Recognition (ICPR), 2018
  43. Zhanfu An and Weihong Deng, Deep Transfer Network with 3D Morphable Models for Face Recognition, IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2018.
  44. Zimeng Luo, Jiani Hu and Weihong Deng, Deep Unsupervised Domain Adaptation for Face Recognition, IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2018.
  45. Weilong Chai and Weihong Deng, Cross-generating GAN for Facial Identity PreservingYichen Qian, IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2018.
  46. Yichen Qian, Weihong Deng and Jiani Hu, Task Specific Networks for Identity and Face Variation, IEEE  International Conference on Automatic Face and Gesture Recognition (FG), 2018.
  47. Weihong Deng, Jiani Hu, Jun Guo, Face Recognition via Collaborative Representation: Its Discriminant Nature and Superposed Representation,  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2017.
  48. Weihong Deng, Jiani Hu, Zhongjun Wu, Jun Guo,  From One to Many: Pose-Aware Metric Learning for Single-Sample Face Recognition, Pattern Recognition (PR), 2017.
  49. Weihong Deng, Yuke Fang, Zhenqi Xu, Jiani Hu,  Facial Landmark Localization by Enhanced Convolutional Neural Network, Neurocomputing, 2017
  50. Weihong Deng, Binghui Chen, Yuke Fang, Jiani Hu, Deep Correlation Feature Learning for Face Verification in the Wild, IEEE Signal Processing Letter, 2017.
  51. Weihong Deng, Jiani Hu, Nanhai Zhang, Binghui Chen, Jun Guo, Fine-grained face verification: FGLFW database, baselines, and human-DCMN partnership. Pattern Recognition (PR), 2017.
  52. Weihong Deng, Jiani Hu, Zhongjun Wu, Jun Guo, Lighting-Aware Face Frontalization for Unconstrained Face Recognition. Pattern Recognition (PR), 2017.
  53. Shan Li, Weihong Deng, Junping Du, Reliable Crowdsourcing and Deep Locality-Preserving Learning for Unconstrained Expression Recognition, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  54. Binghui Chen, Weihong Deng, Junping Du, Noisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  55. Tianyue Zheng, Weihong Deng, Jiani Hu, Age Estimation Guided Convolutional Neural Network for Age-Invariant Face Recognition, CVPR Workshop on Biometrics 2017.
  56. Tianyue Zheng, Weihong Deng and Jiani Hu, Deep Probabilities for Age Estimation, VCIP 2017. (Oral)
  57. Tongtong Yuan, Weihong Deng and Jiani Hu, Supervised Hashing with Extreme Learning, VCIP 2017. (Oral)
  58. Zhanfu An, Weihong Deng and Jiani Hu, Deep Transfer Network for Face Recognition Using 3D Synthesized Face, VCIP 2017. (Oral)
  59. Tongtong Yuan, Weihong Deng, Distortion Minimization Hashing, IEEE Access, 2017
  60. Hongjun Wang, Jiani Hu, Weihong Deng, Compressing Fisher Vector for Robust Face Recognition, IEEE Access, 2017
  61. Yanbing Liao and Weihong Deng, Deep Rank Learning for Facial Attractivenes, ACPR 2017.
  62. Yue Ren, Jiani Hu, Weihong Deng, Facial Expression Intensity Estimation Based on CNN Features and RankBoost, ACPR 2017.
  63. Yukun Ge, Jiani Hu, Weihong Deng, PCA-LDANet: A simple feature learning method for image classification, ACPR 2017.
  64. Yan Wang, Jiani Hu, Weihong Deng, Sum-fusion and Cascaded interpolation for Semantic Image Segmentation, ACPR 2017.
  65. Shuying Liu, Yipeng Huang, Jiani Hu, Weihong Deng, Learning Local Responses of Facial Landmarks with Conditional Variational Auto-Encoder for Face Alignment, The 2nd International Workshop on Biometrics in the Wild 2017 (BWild 2017)
  66. Yipeng Huang, Shuying Liu, Jiani Hu, Weihong Deng, Metric-Promoted Siamese Network for Gender Classification, The 2nd International Workshop on Biometrics in the Wild 2017 (BWild 2017)
  67. Bin Dong, Zhanfu An, Jian Lin, Weihong Deng, Attention-Based Template Adaptation for Face Verification, The 2nd International Workshop on Biometrics in the Wild 2017 (BWild 2017)
  68. Zhiwen Liu, Shan Li, Weihong Deng, Boosting-POOF: Boosting Part Based One vs One Feature for Facial Expression Recognition in the Wild, The 2nd International Workshop on Biometrics in the Wild 2017 (BWild 2017)
  69. Guosheng Hu, Fei Yan, Chi-Ho Chan, Weihong Deng, , William Christmas, Josef Kittler, Neil M. Robertson, Face recognition using a unified 3D morphable model, ECCV 2016
  70. Yida Wang, Can Cui, Xiuzhuang Zhou, Weihong Deng, ZigzagNet: Efficient Deep Learning for Real Object Recognition Based on 3D Models, ACCV 2016
  71. Zhongjun Wu, Weihong Deng, Zhanfu An,  Illumination-Recovered Pose Normalization for Unconstrained Face Recognition, ACCV 2016
  72. Zhenqi Xu, Weihong Deng, Jiani Hu, Learning Facial Point Response for Alignment by Purely Convolutional Network, ACCV 2016
  73. Zhiwen Liu, Shan Li, Weihong Deng, Real-World Facial Expression Recognition using Metric Learning Method, CCBR 2016
  74. Zhiwen Liu, Shan Li, Weihong Deng, Recognizing Compound Emotional Expression in Real-world using Metric Learning Method, CCBR 2016
  75. Nanhai Zhang, Jiajie Han, Jiani Hu, Weihong Deng, Locally Rejected Metric Learning Based False Positives Filtering For Face Detection, CCBR 2016
  76. Shuying Liu, Weihong Deng, Pose Aided Deep Convolutional Neural Networks for face alignment, CCBR 2016
  77. Liao Yanbing, Deng Weihong, and Can Cui, Rank Beauty, CCPR 2016
  78. Tongtong Yuan and Weihong Deng, Robust supervised hashing, A robust supervised hashing, CCPR 2016
  79. Jiajie Han, Jiani Hu and Weihong Deng, Constrained Spectral Clustering on Face Annotation System, CCPR 2016
  80. Yan Gao, Shan Li, Weihong Deng, Intensity estimation of the real-world expression, CCPR 2016
  81. Ling Huang, Songguang Tang, Jiani Hu, Weihong Deng, Saliency Region Detection via Graph Model and Statistical Learning, CCPR 2016
  82. Yida Wang, Weihong Deng, Self-Restraint Object Recognition by Model base CNN Learning, ICIP 2016.
  83. Zhongjun Wu, Weihong Deng, One-shot Deep Neural Network for Pose and Illumination Normalization Face Recognition, IEEE International Conference on Multimeida and Expo (ICME) 2016
  84. Zhenqi Xu, Jiani Hu, Weihong Deng, Recurrent Convolutional Neural Network for Video Classification, IEEE International Conference on Multimeida and Expo (ICME) 2016
  85. Binghui Chen, Weihong Deng, Weakly-Supervised Deep Self-learning for Face Recognition, IEEE International Conference on Multimeida and Expo (ICME) 2016
  86. Nanhai Zhang, Jiajie Han, Jiani Hu, Weihong Deng, Geometry-aware Metric Learning For Similar Face Recognition, IEEE International Conference on Multimeida and Expo (ICME) 2016
  87. Shan Li, Weihong Deng, Real world expression recognition: A highly imbalanced detection problem, 9th IAPR International Conference on Biometrics (ICB), 2016
  88. Nanhai Zhang, Weihong Deng, Fine-grained LFW Database, 9th IAPR International Conference on Biometrics (ICB), 2016
  89. Zhongjun Wu, Weihong Deng,  Adaptive Quotient Image with 3D Generic Elastic Models for Pose and Illumination Invariant Face Recognition, The 10th Chinese Conference on Biometric Recognition, pp. 3-10, 2015
  90. Yida Wang, Shasha Li, Jiani Hu, Weihong Deng. Face Recognition Using Local PCA Filters, The 10th Chinese Conference on Biometric Recognition, pp. 35-42, 2015
  91. Nanhai Zhang, Jiajie Han, Jiani Hu, Weihong Deng, Metric Learning Based False Positives Filtering for Face Detection, 10th Chinese Conference on Biometric Recognition, pp. 60-67, 2015
  92. Hongjun Wang and Weihong Deng, Face Recognition via Compact Fisher Vector, 10th Chinese Conference on Biometric Recognition, pp. 68-77, 2015
  93. Jun Li, Shasha Li, Jiani Hu, Weihong Deng, Simultaneous Blurred Face Restoration and Recognition, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
  94. Hongjun Wang, Jiani Hu and Weihong Deng, Binary Matchin for High-dimensional Image Descriptors, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
  95. Zhenqi Xu, Shan Li, Weihong Deng, Learning Temporal Features Using LSTM-CNN Architecture for Face Anti-spoofing, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
  96. Zhongjun Wu, Shan Li, Weihong Deng, Practical Pose Normalizaiton for Pose-Invariant Face Recognition, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
  97. Shuying Liu, Weihong Deng, Very Deep Convolutional Neural Network Based Image Classification Using Small Training Sample Size, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
  98. Shasha Li, Yukai Tu, Weihong Deng, Jiwen Lu, Noise-resistant local binary pattern based on random projection, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
  99. Shasha Li, Weihong Deng, Face Recognition using Random Features, IEEE Visual Communications and Image Processing (VCIP), 2015.
  100. Weihong Deng, Jiani Hu, Shuo Zhang, Jun Guo, DeepEmo: Real-world Facial Expression Analysis via Deep Learning, IEEE Visual Communications and Image Processing (VCIP), 2015.
  101. Zhongjun Wu, Jiayu Li, Jiani Hu, Weihong Deng Pose-invariant face recognition using 3D multi-depth generic elastic models Automatic Face and Gesture Recognition (FG) 2015: 1-6 2015
  102. Jun Li, Shasha Li, Jiani Hu, Weihong Deng, Adaptive LPQ: An Efficient Descriptor for Blurred Face Recognition, International Conference on Automatic Face and Gesture Recognition, 2015
  103. Jiwen Lu, Gang Wang, Weihong Deng, Kui Jia: Reconstruction-Based Metric Learning for Unconstrained Face Verification. IEEE Transactions on Information Forensics and Security 10(1): 79-89 (2015)
  104. Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, Jie Zhou: Multi-manifold deep metric learning for image set classification. CVPR 2015: 1137-1145
  105. Weihong Deng, Jiani Hu, Jiwen Lu, Jun Guo, Transform-Invariant PCA: A Unified Approach to Fully Automatic Face Alignment, Representation, and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 36, no. 6, pp. 1275–1284, 2014
  106. Weihong Deng, Jiani Hu, Xiuzhuang Zhou, Jun Guo, Equidistant Prototypes Embedding for Single Sample Based Face Recognition with Generic Learning and Incremental Learning, Pattern Recognition (PR),vol 47, no. 12, pp. 3738–3749, 2014.
  107. Haibin Yan, Jiwen Lu, Weihong Deng, Gang Wang, Discriminative multimetric learning for kinship verification[J]. IEEE Transactions on Information forensics and security, 2014, 9(7): 1169-1178.
  108. Jun Li, Chi Zhang, Jiani Hu, Weihong Deng, Blur-Robust Face Recognition via Transformation Learning. ACCV Workshops (3) 2014: 15-29
  109. Liu Liu, Jiani Hu, Shuo Zhang, Weihong Deng, Extended Supervised Descent Method for Robust Face Alignment. ACCV Workshops (3) 2014: 71-84
  110. Zhoucong Cui, Shuo Zhang, Jiani Hu, Weihong Deng, Evaluation of Smile Detection Methods with Images in Real-World Scenarios. ACCV Workshops (3) 2014: 166-179
  111. Weihong Deng, Jiani Hu, Liu Liu, Jun Guo, Transformed Principal Gradient Orientation for Robust and Precise Batch Face Alignment. ACCV (4) 2014: 708-723
  112. Weihong Deng, Jiani Hu, Jun Guo, Linear Ranking Analysis. CVPR 2014: 3638-3645
  113. Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition. ECCV (1) 2014: 265-280
  114. Chi Zhang, Xiang Sun, Jiani Hu, Weihong Deng, Precise eye localization by fast local linear SVM. ICME 2014: 1-6
  115. Jiani Hu, Weihong Deng, Jun Guo, Yajing Xu, Max-K-Min Distance Analysis for Dimension Reduction. ICPR 2014: 726-731
  116. Jiani Hu, Weihong Deng, Jun Guo, Online Regression of Grandmother-Cell Responses with Visual Experience Learning for Face Recognition. ICPR 2014: 4606-4611
  117. Liang Yin, Mingzhi Dong, Ying Duan, Weihong Deng, et al, A high-performance training-free approach for hand gesture recognition with accelerometer, Multimedia Tools Applications, 2013.
  118. Weihong Deng, Jiani Hu, Jun Guo, In Defense of Sparsity Based Face Recognition, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
  119. Mingzhi Dong, Liang Yin, Weihong Deng, et al., A Maximum K-Min Approach for Classification, AAAI 2013
  120. Weihong Deng, Jiani Hu, Jun Guo: Extended SRC: Undersampled Face Recognition via Intraclass Variant Dictionary. IEEE Trans. Pattern Anal. Mach. Intell. 34(9): 1864-1870 (2012)
  121. Weihong Deng, Yebin Liu, Jiani Hu, Jun Guo: The small sample size problem of ICA: A comparative study and analysis. Pattern Recognition 45(12): 4438-4450 (2012)
  122. Liang Yin, Mingzhi Dong, Weihong Deng, Jun Guo, Bin Zhang: Statistical Color Model Based Adult Video Filter. ICME Workshops 2012: 349-353
  123. Mingzhi Dong, Liang Yin, Weihong Deng, Jun Guo, Weiran Xu: A Computationally Efficient Algorithm for Building Statistical Color Models. ICME Workshops 2012: 402-407
  124. Jiani Hu, Weihong Deng, Jun Guo, “Robust eye detection via sparse representation”, in proceedings of the 3rd IEEE International Conference on Network Infrastructure and Digital Content, pp.411-415, 2012.
  125. Jiani Hu, Weihong Deng, Jun Guo,  “A semi-supervised clustering algorithm based on local scaling graph and label propagation”, in Proceedings of International Conference on Computer Science and Network Technology, pp.1059-1062, 2011.
  126. Hu, Jiani; Deng, Weihong; Guo, Jun, “2D projective transformation based active shape model for facial feature location”, in Proceedings of 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, v 4, p 2442-2446, 2011.
  127. Weihong Deng, Jiani Hu, Jun Guo, Weidong Cai, Dagan Feng, “Robust, accurate and efficient face recognition from a single training image: A uniform pursuit approach”, Pattern Recognition, vol. 43. no. 5, pp. 1748-1762, 2010.
  128. Weihong Deng, Jiani Hu, Jun Guo, Weidong Cai, Dagan Feng, “Emulating biological strategies for uncontrolled face recognition”, Pattern Recognition, vol. 43. no. 6, pp. 2210-2223, 2010.
  129. Honggang Zhang, Weihong Deng, Jun Guo, Jie Yang, “Locality preserving and global discriminant projection with prior information”, MACHINE VISION AND APPLICATIONS, Vol.21, No.4, pp.577-585, 2010.
  130. Hu Jiani, Li Yu, Deng Weihong, Guo Jun, Xu Weiran, “Locating facial features by robust active shape model”, 2nd IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2010, pp. 196-200, 2010.
  131. 高精度人脸识别算法研究,北京邮电大学博士学位论文(北京市优秀博士学位论文)。
  132. Jiani Hu, Weihong Deng, Jun Guo, etc. Learning a Locality Discriminating Projection for Classification, Knowledge-Based Systems, Elsevier, vol. 22, no. 8, pp.562-568, 2009.
  133. Jiani Hu, Weihong Deng, Jun Guo. Semi-Supervised Learning Based on Label Propagation through Submanifold, Sixth International Symposium on Neural Networks, Part I, LNCS 5551, pp. 617-623, 2009.
  134. Weihong Deng, Jun Guo, Jiani Hu, Hongang Zhang, “Comment on “100% Accuracy in Automatic Face Recognition””, Science, vol. 321. no. 5891, pp. 912, 2008
  135. Weihong Deng, Jiani Hu, Jun Guo, Hongang Zhang, Chuang Zhang, “Comments on “Globally Maximizing, Locally Minimizing: Unsupervised Discriminant Projection with Application to Face and Palm Biometrics””, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30. no. 8, pp. 1503-1504, 2008.
  136. Jiani Hu, Weihong Deng, Jun Guo, etc, “Locality Discriminating Indexing for Document Classification” The 30th Annual International ACM Conference on Research and Development in Information Retrieval (SIGIR’ 07), pp.689-690, 2007.
  137. Jiani Hu, Weihong Deng, Jun Guo, etc, “Learning Locality Discriminating Indexing for Text Categorization” The 4th International Conference on Fuzzy Systems and Knowledge Discovery, 2007, pp. 239-242.
  138. Jiani Hu, Weihong Deng, Jun Guo, “A Clustering Algorithm Based on Adaptive Subcluster Merging” The 20th Canadian Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence, vol. 4509, pp. 241-249, 2007.
  139. 胡佳妮,郭军,邓伟洪,徐蔚然,“基于短文本的独立语义特征抽取算”,通信学报,28(12),pp.121-124, 2007.
  140. Weihong Deng, Jiani Hu, Jun Guo, “Robust Discriminant Analysis o f Gabor Feature for Face Recognition” The 4th International Conference on Fuzzy Systems and Knowledge Discovery, vol.3, pp248-252, 2007.
  141. Jiani Hu, Weihong Deng, Jun Guo, “Improving Retrieval Performance by Global Analysis” Proceeding of the 18th International Conference on Pattern Recognition (ICPR2006), vol. 2, pp. 703–706, 2006.
  142. Jiani Hu, Weihong Deng, Jun Guo, “Robust Discriminant Analysis of Latent Semantic Feature for Text Categorization”, The 3rd International Conference on Fuzzy Systems and Knowledge Discovery, Lecture Notes in Artificial Intelligence, vol. 4223, pp. 400–409, 2006.
  143. Weihong Deng, Jiani Hu, Jun Guo, “Gabor Feature Based Classification using LDA/QZ Algorithm for Face Recognition” The 2nd International Conference on Natural Computation, Lecture Notes in Computer Science, Vol. 4221, pp. 15–24, 2006.
  144. Weihong Deng, Jiani Hu, Jun Guo, “Robust fisher linear discriminant model for dimensionality reduction”, International Conference on Pattern Recognition, v 2, p 699-702, 2006, Proceedings – 18th International Conference on Pattern Recognition, ICPR2006
  145. Weihong Deng, Jiani Hu, Jun Guo, Gabor-Eigen-Whiten-Cosine: A Robust Scheme for Face Recognition. IEEE International Workshop on Analysis and Modeling of Faces and Gestures conjuncted with ICCV2005,(AMFG2005), Lecture Notes in Computer Science, Vol. 3723. (Oct. 2005) pp.336-349.
  146. Weihong Deng, Jiani Hu, Jun Guo, Robust Face Recognition from One Training Sample per Person, First International Conference on Natural Computation (ICNC’05), Lecture Notes in Computer Science, Vol. 3610. (July, 2005) pp.915-924.

指导在读学生

  • 博士后:李珊
  • 博士生:钟瑶瑶,王玫,赵钰莹,刘炳宇,江静,张宇航
  • 张耀斌,方瀚,范弘炜,牛逸凡,于泽辉,王卓
  • 陆奕辰、袁小童、梁嘉豪、王成瑞、高子键、李思奇
  • 李茜曼、凌旭、郭思涵、洪世勇、黄林志、田宏博

QQ图片20151222085300 20160331_155546QQ图片20151222085638 QQ图片20151222085328QQ图片20151225232735  

毕业学生

  • 读博:董明智 UCL,徐翔 UH,李莎莎 UCR,蔡佳芮 UW,李昱 NUS,王婧 Michigan,王一达 TUM,黄泄合
  • 读研:张硕 Cambridge [IET年度优秀学生],李嘉钰、邱淑雯 UCLA,陈脱颖 UCSD,钱尘 Stanford,曾翔宇 Columbia,姜晟浩 Harvard,孙祥、于世莲 清华大学
  • 百度:阴凉,黄凌,林坚,郑天悦,白雪,陈路燕
  • 阿里:刘柳,李靖意,张南海,钱一琛,陈炳辉,柴维珑,曲岩
  • 腾讯:李昱,黄义鹏,杨善明
  • 网易:邬仲钧,刘书颖,董彬
  • 头条:徐珍琦,廖艳冰,葛煜坤,孙祥
  • 美团:张振华,葛建成
  • 滴滴:王艳,李剑,田万鑫,黄泄合
  • 微软:张驰,王远
  • Momenta:李俊,韩嘉杰
  • 袁彤彤(北工大),罗子朦(旷视),刘智雯(vivo)

附1:人工智能学术讨论

附2:研究生培养的主要能力(保送或读研考核

  • 编程实践能力:无论是算法还是工程,动手和折腾是做好本领域研究的首要能力,要求本科期间的编程作业均为独立完成,读研期间需要做大量的编程来验证想法的合理性。
  • 心态调整能力:本小组比较侧重科研创新和论文发表,要求同学们有持续完善研究课题的耐心和热情。
  • 较强英语文献自学和表达能力、基础数学理解和推导能力。
  • 认识研究生与本科生学习的区别,如何充实地完成研究生学业?学生角度导师角度 / 人生角度
  • 2018届研究生毕业典礼导师代表发言: “人工智能”的坚毅和独立思考

附3:计算机视觉应用领域(学生主要就业方向)