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With fifteen years’ research and development experience
on computer vision and pattern recognition,
we mainly work on two areas.
- Trustworthy AI has attracted immense attention recently, which aims to let humans can fully trust and live in harmony with AI technologies. To pursuit this goal, we conduct research on various dimensions: (i) Robustness & Reliability, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Security & Privacy, etc.
- Human Sensing. Human plays a central role in computer vision applications. We aim to develop advanced methods to recognize and understand human and their behaviors from image and video. Our work is motivated by applications in the fields of video surveilance, human health, biometrics and human-machine interface.
Survey on Face Recognition
Survey on Transfer Learning
Racial Bias in Face Recognition
Survey on Expression Recognition
Compound Facial Expression in-the-Wild
Blended Facial Expression in-the-Wild
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Person ReID
Re-Identify persons across cameras in video surveillance...
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(Google Scholar Profile)
(DBLP)
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Journal Papers
- 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, DOI: 10.1007/s11263-018-1131-1
- 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), DOI: 10.1109/TPAMI.2018.2800008, 2019.
- Tongtong Yuan, Weihong Deng, Jiani Hu, Zhanfu An, Yinan Tang, Unsupervised Adaptive Hashing Based on Feature Clustering, Neurocomputing, 2019
- Shan Li, Weihong Deng, Reliable Crowdsourcing and Deep Locality-Preserving Learning for Unconstrained Facial Expression Recognition, IEEE Transactions on Image Processing (TIP), 28(1):356-370, 2019.
- Yida Wang, Weihong Deng, Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models, IEEE Transactions on Image Processing (TIP), 27(12): 5813-5826, 2018.
- Weihong Deng, Hongjun Wang, Face recognition with compressed Fisher vector on multiscale convolutional features. IET Biometrics 7(5): 447-453, 2018
- Mei Wang, Weihong Deng, Deep Visual Domain Adaptation: A Survey, Neurocomputing, 312: 135-153 (2018)
- Hongjun Wang, Jiani Hu, Weihong Deng, Face Feature Extraction: A Complete Review. IEEE Access 6: 6001-6039, 2018.
- 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.
- Weihong Deng, Jiani Hu, Zhongjun Wu, Jun Guo, From One to Many: Pose-Aware Metric
Learning for
Single-Sample Face Recognition, Pattern Recognition (PR), vol. 77, pp.
426-437, 2018
- Weihong Deng Yuke Fang, Zhenqi Xu, Jiani Hu, Facial Landmark
Localization by Enhanced
Convolutional Neural Network, Neurocomputing, 2017
- Weihong Deng, Binghui Chen, Yuke Fang, Jiani Hu, Deep Correlation
Feature Learning
for Face Verification in the Wild, IEEE Signal Processing Letter, 2017.
- Tongtong Yuan, Weihong Deng, Distortion Minimization Hashing,
IEEE Access, 2017
- Hongjun Wang, Jiani Hu, Weihong Deng, Compressing Fisher Vector
for Robust Face
Recognition, IEEE Access, 2017
- Weihong Deng, Jiani Hu, Nanhai Zhang, Binghui Chen, Jun Guo,
Fine-grained face
verification: FGLFW database, baselines, and human-DCMN partnership.Pattern Recognition (PR), vol. 66, pp. 63-73, 2017.
- Weihong Deng, Jiani Hu, Zhongjun Wu, Jun Guo, Lighting-Aware Face
Frontalization for
Unconstrained Face Recognition. Pattern Recognition (PR), vol. 68, pp.
260-271, 2017.
- Wenming Yang, Xiang Sun, Weihong Deng, Chi Zhang, Qingmin Liao, Fourier locally linear soft constrained MACE for facial landmark localization, CAAI Transactions on Intelligence Technology, vol. 1, no. 3, pp. 241-248, 2016.
- Jiwen Lu, Gang Wang, Weihong Deng, Kui Jia: Reconstruction-Based
Metric Learning for
Unconstrained Face Verification. IEEE Transactions on Information Forensics and Security (TIFS)
10(1): 79-89 (2015)
- Haibin Yan, Jiwen Lu, Weihong Deng, Xiuzhuang zhou,
Discriminative Multi-Metric
Learning for Kinship Verification, IEEE Transactions on Information Forensics and
Security (TIFS), 2014
- 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.
- 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.
- 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.
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Weihong Deng, Jiani Hu, Jun Guo, "Extended SRC:
Undersampled Face
Recognition via Intra-Class Variant Dictionary," IEEE Transactions on Pattern
Analysis and Machine
Intelligence (PAMI), vol. 34, no. 9, pp. 1864-1870, 2012.
- Weihong Deng, Yebin Liu, Jiani Hu, Jun Guo, "The
Small Sample Size Problem of ICA: A comparative study and analysis",Pattern Recognition (PR), vol. 45, no. 12, pp. 4438-4450, 2012.
- 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 (PR), vol. 43.
no. 5, pp. 1748-1762,
2010.
- Weihong Deng, Jiani Hu, Jun Guo, Weidong Cai, Dagan Feng,
"Emulating biological strategies for uncontrolled face
recognition",Pattern Recognition (PR), vol. 43. no. 6, pp. 2210-2223, 2010.
- 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.
- Jiani Hu, Weihong Deng, Jun Guo, Weiran Xu. Learning a Locality
Discriminating
Projection for Classication, Knowledge-Based Systems, vol. 22, no. 8, pp. 562-568, 2009.
- Weihong Deng, Jiani Hu, Jun Guo, "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.
- Weihong Deng, Jun Guo, Jiani Hu, "Comment on "100%
Accuracy in Automatic
Face Recognition"", SCIENCE, vol. 321. no. 5891, pp. 912,
2008
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Conference Papers
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- Mei Wang, Weihong Deng, et al., Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation Network, ICCV 2019.
- Bingyu Liu, Weihong Deng, et al., Fair Loss: Margin-aware Reinforcement Learning for Deep Face Recognition, ICCV 2019.
- Yaoyao Zhong, Weihong Deng, et al., Adversarial Learning with Margin-based Triplet Embedding Regularization, ICCV 2019.
- Binghui Chen, Weihong Deng, et al., Mixed High-Order Attention Network for Person Re-Identification, ICCV 2019.
- Tongtong Yuan, Weihong Deng, Jiani Hu, et al., Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning, CVPR 2019.
- Binghui Chen, Weihong Deng, Hybrid-Attention based Decoupled Embedding Learning for Zero-Shot Image Retrieval, CVPR 2019.
- Yichen Qian, Weihong Deng, Mei Wang, Jiani Hu, Haifeng Shen, Unsupervised Face Normalization with Extreme Pose and Expression in the Wild, CVPR 2019.
- Yaoyao Zhong, Weihong Deng,Mei Wang, Jiani Hu, Xunqiang Tao, Jianteng Peng, Yaohai Huang, Unequal-training for deep face recognition with long-tailed noisy data, CVPR 2019.
- Binghui Chen, Weihong Deng, Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering, AAAI, 2019.
- Binghui Chen, Weihong Deng, Haifeng Shen, Virtual Class Enhanced Discriminative Embedding Learning, NIPS 2018 (Spotlight)
- Shan Li, Weihong Deng, Deep Emotion Transfer Network for Cross-database Facial Expression Recognition, International Conference on Pattern Recognition (ICPR), 2018.
- Zimeng Luo, Jiani Hu, Weihong Deng, Local Subclass Constraint for Facial Expression Recognition in the Wild, International Conference on Pattern Recognition (ICPR), 2018.
- Yaoyao Zhong, Weihong Deng, Deep Difference Analysis in Similar-looking Face recognition, International Conference on Pattern Recognition (ICPR), 2018
- Shuwen Qiu, Weihong Deng, Deep Local Descriptors with Domain Adaptation. PRCV (2) 2018: 344-355
- 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.
- 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.
- Weilong Chai and Weihong Deng, Cross-generating GAN for Facial Identity PreservingYichen Qian, IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2018.
- 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.
- 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.
- 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.
- Tianyue Zheng, Weihong Deng, Jiani Hu, Age Estimation Guided Convolutional Neural Network for Age-Invariant Face Recognition, CVPR Workshop on Biometrics 2017.
- Tianyue Zheng, Weihong Deng and Jiani Hu, Deep Probabilities for Age Estimation, VCIP 2017. (Oral)
- Tongtong Yuan, Weihong Deng and Jiani Hu, Supervised Hashing with Extreme Learning, VCIP 2017. (Oral)
- Zhanfu An, Weihong Deng and Jiani Hu, Deep Transfer Network for Face Recognition Using 3D Synthesized Face, VCIP 2017. (Oral)
- Yanbing Liao and Weihong Deng, Deep Rank Learning for Facial Attractivenes, ACPR 2017.
- Yue Ren, Jiani Hu, Weihong Deng, Facial Expression Intensity Estimation Based on CNN Features and RankBoost, ACPR 2017.
- Yukun Ge, Jiani Hu, Weihong Deng, PCA-LDANet: A simple feature learning method for image classification, ACPR 2017.
- Yan Wang, Jiani Hu, Weihong Deng, Sum-fusion and Cascaded interpolation for Semantic Image Segmentation, ACPR 2017.
- 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)
- 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)
- 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)
- 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)
- 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
- Yida Wang, Can Cui, Xiuzhuang Zhou, Weihong Deng, ZigzagNet: Efficient Deep Learning for Real Object Recognition Based on 3D Models, ACCV 2016
- Zhongjun Wu, Weihong Deng, Zhanfu An, Illumination-Recovered Pose Normalization for Unconstrained Face Recognition, ACCV 2016
- Zhenqi Xu, Weihong Deng, Jiani Hu, Learning Facial Point Response for Alignment by Purely Convolutional Network, ACCV 2016
- Zhiwen Liu, Shan Li, Weihong Deng, Real-World Facial Expression Recognition using Metric Learning Method, CCBR 2016
- Zhiwen Liu, Shan Li, Weihong Deng, Recognizing Compound Emotional Expression in Real-world using Metric Learning Method, CCBR 2016
- Nanhai Zhang, Jiajie Han, Jiani Hu, Weihong Deng, Locally Rejected Metric Learning Based False Positives Filtering For Face Detection, CCBR 2016
- Shuying Liu, Weihong Deng, Pose Aided Deep Convolutional Neural Networks for face alignment, CCBR 2016
- Liao Yanbing, Weihong Deng, and Can Cui, Rank Beauty, CCPR 2016
- Tongtong Yuan and Weihong Deng, Robust supervised hashing, A robust supervised hashing, CCPR 2016
- Jiajie Han, Jiani Hu and Weihong Deng, Constrained Spectral Clustering on Face Annotation System, CCPR 2016
- Yan Gao, Shan Li, Weihong Deng, Intensity estimation of the real-world expression, CCPR 2016
- Ling Huang, Songguang Tang, Jiani Hu, Weihong Deng, Saliency Region Detection via Graph Model and Statistical Learning, CCPR 2016
- Yida Wang, Weihong Deng, Self-Restraint Object Recognition by Model base CNN Learning, ICIP 2016.
- 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
- Zhenqi Xu, Jiani Hu, Weihong Deng, Recurrent Convolutional Neural Network for Video Classification, IEEE International Conference on Multimeida and Expo (ICME) 2016
- Binghui Chen, Weihong Deng, Weakly-Supervised Deep Self-learning for Face Recognition, IEEE International Conference on Multimeida and Expo (ICME) 2016
- 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
- Shan Li, Weihong Deng, Real world expression recognition: A highly imbalanced detection problem, 9th IAPR International Conference on Biometrics (ICB), 2016
- Nanhai Zhang, Weihong Deng, Fine-grained LFW Database, 9th IAPR International Conference on Biometrics (ICB), 2016
- 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
- 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
- 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
- Hongjun Wang and Weihong Deng, Face Recognition via Compact Fisher Vector, 10th Chinese Conference on Biometric Recognition, pp. 68-77, 2015
- Jun Li, Shasha Li, Jiani Hu, Weihong Deng, Simultaneous Blurred Face Restoration and Recognition, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
- Hongjun Wang, Jiani Hu and Weihong Deng, Binary Matchin for High-dimensional Image Descriptors, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
- 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
- Zhongjun Wu, Shan Li, Weihong Deng, Practical Pose Normalizaiton for Pose-Invariant Face Recognition, 3rd Asian Conference on Pattern Recognition (ACPR), 2015
- 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
- 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
- Shasha Li, Weihong Deng, Face Recognition using Random Features, IEEE Visual Communications and Image Processing (VCIP), 2015.
- 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.
- 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
- 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
- Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, Jie Zhou: Multi-manifold deep metric learning for image set classification. CVPR 2015: 1137-1145
- Weihong Deng, Jiani Hu, Liu Liu, Jun Guo, Transformed Principal
Gradient Orientation
for Robust and Precise Batch Face Alignment, ACCV, 2014.
- Jiwen Lu, Wang Gang, Weihong Deng, et al.Simultaneous Feature and
Dictionary Learning
for Image Set Based Face Recognition, ECCV, 2014.
- Weihong Deng, Jiani Hu, Jun Guo, Linear
Ranking
Analysis, IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
2014. [poster]
- Weihong Deng, Jiani Hu, Jun Guo, In
Defense of Sparsity
Based Face Recognition, IEEE Conference on Computer Vision and Pattern
Recognition
(CVPR), 2013.
- Jun Li, Chi Zhang, Jiani Hu, Weihong Deng, Blur-Robust Face
Recognition via
Transformation Learning, ACCV Workshop on Feature and Similarity Learning for Computer
Vision, Singapore,
Nov. 2014.
- Liu Liu, Jiani Hu, Shuo Zhang, Weihong Deng, Extended Supervised
Descent Method for
Robust Face Alignment, ACCV Workshop on Feature and Similarity Learning for Computer
Vision, Singapore, Nov.
2014.
- Zhoucong Cui, Shuo Zhang, Jiani Hu, Weihong Deng, Evaluation of
Smile Detection
Methods with Images in Real-world Scenarios, ACCV Workshop on Feature and Similarity
Learning for Computer
Vision, Singapore, Nov. 2014.
- Jiani Hu,Weihong Deng, Jun Guo, Yajing Xu, Max-K-Min Distance
Analysis for Dimension
Reduction, ICPR 2014
- Jiani Hu,Weihong Deng, Jun Guo, Online Regression of
Grandmother-Cell Responses with
Visual Experience Learning for Face Recognition, ICPR 2014
- Chi Zhang, Xiang Sun, Jiani Hu, Weihong Deng, Precise eye
localization by fast local
linear SVM, ICME 2014.
- Liang Yin, Mingzhi Dong,Weihong Deng, Jun Guo, Bin Zhang:
Statistical Color Model
Based Adult Video Filter. ICME Workshops 2012: 349-353
- Mingzhi Dong, Liang Yin,Weihong Deng, et al., A Maximum K-Min
Approach for
Classification, AAAI 2013
- Mingzhi Dong, Liang Yin,Weihong Deng, Jun Guo, Weiran Xu: A
Computationally Efficient
Algorithm for Building Statistical Color Models. ICME Workshops 2012
- Mingzhi Dong, Liang Yin, Jun Guo,Weihong Deng, Weiran Xu:
Integrative labeling based
statistical color models with application to skin detection. ICIP 2012: 2369-2372
- Mingzhi Dong, Liang Yin,Weihong Deng, Qiang Wang, Caixia Yuan,
Jun Guo, Li Shang,
Liwei Ma: A Linear Max K-min classifier. ICPR 2012: 2967-2971
- Jiani Hu,Weihong Deng, 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, vol 4, p 2442-2446, 2011.
- Jiani Hu, Yu Li, Weihong Deng, 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- 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.
- 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.
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| Racial Faces in-the-Wild (RFW)
Racial Faces in-the-Wild (RFW) is a large-scale face database for studying racial bias in face recognition which has two important uses: 1) Measure racial bias of FR algorithms. 2) Promote to reduce racial bias by transfer learning.
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| Real-world Affective Faces Database (RAF-DB)
Real-world Affective Faces Database (RAF-DB) is a large-scale dataset that contains around 20k facial images downloaded from the Internet. With manually crowd-sourced annotation and reliable estimation, seven basic expressions and eleven compound expressions are presented which contain great variability in subjects' identity, head poses, lighting conditions, occlusions and so on.
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| Real-world Affective Faces Multi Label (RAF-ML)
Real-world Affective Faces Multi Label (RAF-ML) is a multi-label dataset that contains various facial images with blended emotions from the Internet. Via manually crowd-sourced annotation and reliable estimation, multiple expression label and probability distribution are provided for each sample. Specifically, the number of images with two, three and four labels are 3954, 913 and 41, respectively.
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| Similar-Looking Labelled Faces in-the-Wild (SLLFW) DEMO GAME
The data set searches and selects 3,000 similar-looking negative face pairs from the original LFW image collection, by a crowdsourcing work of 300 students. Negative pairs with same gender and race are also selected to reduce the influence of attribute difference between positive/negative pairs. The 3000 positive pairs are identical to the well-known LFW benchmark. It share the same image collection with LFW, so one can easily apply SLLFW to evaluate the performance of face verification. |
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| Cross-Age Labelled Faces in-the-Wild (CALFW)
The data set searches and selects 3,000 positive face pairs with age difference to add age variation to intra-class variance. Negative pairs with same gender and race are also selected to reduce the influence of attribute difference between positive/negative pairs. It Maintains the data size, the face verification protocol which provides a 'same/different' benchmark and the same identities in LFW, so one can easily apply CALFW to evaluate the performance of face verification.
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| Cross-Pose Labelled Faces in-the-Wild (CPLFW)
The data set searches and selects 3,000 positive face pairs with pose difference to add pose variation to intra-class variance. Negative pairs with same gender and race are also selected to reduce the influence of attribute difference between positive/negative pairs. It Maintains the data size, the face verification protocol which provides a 'same/different' benchmark and the same identities in LFW, so one can easily apply CPLFW to evaluate the performance of face verification. |
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| FERET-aligned
The FERET Image aligned by TIPCA technique that learn the coding bases invariant to the transformation of the training images, leading to improved alignment, coding, and recognition performance
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I teach two courses regularly each year as follows.
1. Neural network and fuzzy systems (Postgraduate Fall semester)
- Basics of Machine Learning (CUHK-slide, Stanford-slide)
- MLP, Backpropagation, Loss funcions (CUHK-slide, Stanford-slide)
- Optimization for Training Deep Models(CUHK-slide, Stanford-slide)
- Autoencoder(CUHK-slide)
- CNN architectures (CUHK-slide, cs231n-cnn-basics, cs231n-cnn-architect, CNN_BP),Stanford-slide,Stanford-slide)
- Loss function(cs231n-slide, Stanford-slide)
- Deep learning software frameworks (Tensorflow, Pytorch)
- RNN, LSTM, Attention (CUHK-slide)
- Self Attention, Transformer (cs231n-notes)
- Graph Neural Network (Stanford-notes)
- Deep reinforcement learning (cs231n-notes)
- Generative Adversarial Network (cs231n-notes)
- Deep domain adaptation (survey_paper, ppt, video) [detailed chinese notes_1 note_2]
- Advanced topics on Guest Lectures (Face)
2. Pattern Recognition and Applications (Undergraduate Spring semester)
Comming soon
