Full list see

Selected Publication List

1 Journal Articles

Selected Publications in 2023

· G Zhu, R Wang, Y Liu, Z Zhu, C Gao, L Liu, N Sang, An Adaptive Postprocessing Network with the Global-Local Aggregation for Semantic Segmentation, IEEE Transactions on Circuits and Systems for Video Technology, 2023.

· Y Sun, L Lei, L Liu, G Kuang, Structural Regression Fusion for Unsupervised Multimodal Change Detection, IEEE Transactions on Geoscience and Remote Sensing, 2023.

· S Sun, S Zhi, Q Liao, J Heikkila, L Liu, Unbiased Scene Graph Generation via Two-stage Causal Modeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

· Y Cui, W Deng, H Chen, L Liu, Uncertainty-Aware Distillation for Semi-Supervised Few-Shot Class-Incremental Learning, IEEE Transactions on Neural Networks and Learning Systems, 2023.

· Q Luo, H He, K Liu, C Yang, O Silven, L Liu, Rain like Layer Removal from Hot Rolled Steel Strip Based on Attentive Dual Residual Generative Adversarial Network, IEEE Transactions on Instrumentation and Measurement, 2023.

· C Xiao, T Liu, X Ying, Y Wang, M Li, L Liu, W An, Z Chen, Incorporating Deep Background Prior Into Model-Based Method for Unsupervised Moving Vehicle Detection in Satellite Videos, IEEE Transactions on Geoscience and Remote Sensing, 2023.

Selected Publications in 2022

· J Liu, B Sun, G Liu, X Dong, L Liu, H Zhang, C Li, New Wine Old Bottles: Feistel Structure Revised, IEEE Transactions on Information Theory, 2022.

· Y Sun, L Lei, D Guan, G Kuang, L Liu, Graph Signal Processing for Heterogeneous Change Detection, IEEE Transactions on Geoscience and Remote Sensing, 2022.

· W Chen, H Xu, N Pu, Y Liu, M Lao, W Wang, L Liu, MS Lew, Lifelong Fine grained Image Retrieval, IEEE Transactions on Multimedia, 2022.

· W Chen, Y Liu, W Wang, EM Bakker, T Georgiou, P Fieguth, L Liu, MS Lew, Deep learning for instance retrieval: A survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022.

· X Wu, X Zhang, X Feng, MB Lopez, L Liu, Audio-Visual Kinship Verification: a New Dataset and a Unified Adaptive Adversarial Multimodal Learning Approach, IEEE Transactions on Cybernetics, 2022.

· H Chai, Z Yin, Y Ding, L Liu, B Fang, Q Liao, A Model Agnostic Approach to Mitigate Gradient Interference for Multi-Task Learning, IEEE Transactions on Cybernetics, 2022.

· B Peng, B Peng, J Zhou, J Xie, L Liu, Scattering Model Guided Adversarial Examples for SAR Target Recognition: Attack and Defense, IEEE Transactions on Geoscience and Remote Sensing, 2022.

· C Sheng, L Liu, W Deng, L Bai, Z Liu, S Lao, G Kuang, M Pietikainen, Importance Aware Information Bottleneck Learning Paradigm for Lip Reading, IEEE Transactions on Multimedia, 2022.

· Y Cui, W Deng, X Xu, Z Liu, Z Liu, M Pietikainen, L Liu, Uncertainty Guided Semisupervised Few Shot Class Incremental Learning with Knowledge Distillation, IEEE Transactions on Multimedia, 2022.

· R Chen, J Li, H Zhang, C Sheng, L Liu, X Cao, Sim2Word: Explaining Similarity with Representative Attribute Words via Counterfactual Explanations, ACM Transactions on Multimedia Computing Communications and Applications, 2022.

· Q Luo, J Su, C Yang, O Silven, L Liu, Scale Selective and Noise Robust Extended Local Binary Pattern for Texture Classification, Pattern Recognition, 2022.

· Y Wang, A Abliz, H Ma, L Liu, A Kurban, U Halik, M Pietikainen, W Wang, Hyperspectral Estimation of Soil Copperconcentration based on ImprovedTabNet Model in the Eastern Junggar Coalfield, IEEE Transaction on Geoscience and Remote Sensing, 2022.

· Y Sun, L Lei, D Guan, J Wu, G Kuang, L Liu, Image Regression with Structure Cycle Consistency for Heterogeneous Change Detection, IEEE Transactions on Neural Networks and Learning Systems, 2022.

· Q Luo, J Su, C Yang, W Gui, O Silven, L Liu, CATEDNet: Cross Attention Transformer based Encoder-Decoder Network for Salient Defect Detection of Strip Steel Surface, IEEE Transactions on Instrumentation and Measurement, 2022.

· X Wu, X Feng, X Cao, X Xu, D Hu, MB Lopez, L Liu, Facial Kinship Verification: A Comprehensive Review and Outlook, International Journal of Computer Vision, 2022.

· Y Zhao, L Zhao, Z Liu, D Hu, G Kuang, L Liu, Attentional Feature Refinement and Alignment Network for Aircraft Detection in SAR Imagery, IEEE Transactions on Geoscience and Remote Sensing, 2022.

Selected Publications in 2021

· W. Deng, Q. Liao, L. Zhao, D. Guo, G. Kuang, D. Hu, Li Liu, Joint Clustering and Discriminative Feature Alignment for Unsupervised Domain Adaptation, IEEE Transactions on Image Processing, 2021.

· Y. Zhao, L. Zhao, Z. Liu, D. Hu, G. Kuang, Li Liu, Attentional Feature Refinement and AlignmentNetwork for Aircraft Detection in SAR Imagery, IEEE Transactions on Geoscience and Remote Sensing.

· S Liu, X Liu, L Liu, S Zhou, E Zhu, Late Fusion Multiple Kernel Clustering with Proxy Graph Refinement, IEEE Transactions on Neural Networks and Learning Systems, 2021.

· L. Zhang, X. Leng, S. Feng, X. Ma, K. Ji, G. Kuang, Li Liu, Domain Knowledge Powered Two-Stream Deep Network for Few-Shot SAR Vehicle Recognition, IEEE Transactions on Geoscience and Remote Sensing, Accepted.

· Y. Cui, Q. Liao, D. Hu, W. An, Li Liu, Exploring Coarse to Fine Pseudo Supervisions for Unsupervised Few Shot Object Classification, Pattern Recognition, 2021.

· Q. Luo, K. Liu, J. Su, C. Yang, W. Gui, Li Liu, O. Silven, Waterdrop Removal from Hot Rolled Steel Strip Surfaces based on Progressive Recurrent Generative Adversarial Networks, IEEE Transactions on Instrumentation and Measurement, 2021.

· C. Sheng, X. Zhu, H. Xu, M. Pietikäinen, Li Liu, Adaptive Semantic-Spatio-Temporal Graph Convolutional Network for Lip Reading, IEEE Transactions on MultiMedia, 2021.

· C. Chen, S. Dong, Y. Tian, K. Cao, Li Liu, Y. Guo, Temporal SelfEnsembling Teacher for Semisupervised Object Detection, IEEE Transactions on Multimedia, 2021.

· W. Deng, L. Zhao, Q. Liao, D. Guo, G. Kuang, D. Hu, M. Pietikäinen, Li Liu, Informative Feature Disentanglement for Unsupervised Domain Adaptation, IEEE Transactions on Multimedia, 2021.

· W. Chen, Y. Liu, N. Pu, W. Wang, Li Liu M. Lew, Feature Estimations based Correlation Distillation for Incremental Image Retrieval, IEEE Transactions on MultiMedia, 2021.

· M. Abdar, F. Pourpanah, S. Hussain, D. Rezazadegan, Li Liu, M. Ghavamzadeh, P. Fieguth, A. Khosravi, U. R. Acharya, V. Makarenkov, S. Nahavandi, A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges, Information Fusion, vol. 76, pp. 243-297, 2021.

· W. Deng, Z. Su, L. Zhao, G. Kuang, M. Pietikäinen, Li Liu, Deep Ladder-Suppression Network for Unsupervised Domain Adaptation, IEEE Transactions on Cybernetics, 2021.

Publications in 2020

· S Gao, Q Ye, Li Liu, A Kuijper, X Ji,A Graphical Social Topology Model for RGB-D MultiObject Tracking, IEEE Transactions on Circuits and Systems for Video Technology, 2020.pdf

· J Cai, H Han, J Cui, J Chen, Li Liu, S Zhou, Semisupervised Natural Face Deocclusion,IEEE Transactions on Information Forensics and Security, 2020.pdf

· Li Liu, M Pietikäinen, J Qin, W Ouyang, LV Gool, Guest Editorial: Efficient Visual Recognition, International Journal of Computer Vision, 2020.pdf

· W Chen, W Wang, Li Liu, MS Lew,New Ideas and Trends in Deep Multimodal Content Understanding: A Review,Neurocomputing, 2020.pdf

· M Tavakoliana, MB Lopezb, Li Liu,Selfsupervised pain intensity estimation from facial videos via statistical spatiotemporal distillation,Pattern Recognition Letters, 2020.pdf

· Q Luo, X Fang, J Su, J Zhou, B Zhou, C Yang, Li Liu, W Gui, L Tian ,Automated Visual Defect Classification for Flat Steel Surface: A Survey,IEEE Transactions on Instrumentation and Measurement, 2020.pdf

· Y. Guo, H. Wang, Q. Hu, H. Liu, Li Liu, M. Bennamoun, Deep Learning for 3D Point Clouds: A Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.pdf

· Li Liu, M Pietikäinen, J Qin, W Ouyang, LV Gool, Guest Editorial: Efficient Visual Recognition, International Journal of Computer Vision, 2020.pdf

· Li Liu, W. Ouyang, X. Wang, P. Fieguth, J. Chen, X. Liu, M. Pietikäinen, Deep Learning for Generic Object Detection: A Survey, International Journal of Computer Vision, 128 (2), 2020.pdf

· X. Liu, M. Li, C. Tang, J. Xiong, J. Xia, Li Liu, M. Kloft, and E. Zhu, Efficient and Effective Regularized Incomplete Multiview Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.pdf

· S. Zhou, X. Liu, M. Li, E. Zhu, L. Liu, C. Zhang, J. Yin, Multiple Kernel Clustering with Neighbor Kernel Subspace Segmentation, IEEE Transactions on Neural Networks and Learning Systems, 31 (4), 1351-1362, 2020.pdf

· J. Sui, Z Liu, Li Liu, A. Jung, X. Li, Dynamic Sparse Subspace Clustering for Evolving High dimensional Data Streams, IEEE Transactions on Cybernetics, 1-14, 2020.pdf

· L. Wang, Y. Guo, Li Liu, Z. Lin, X. Deng, W. An, Deep Video Superresolution using HR Optical Flow Estimation, IEEE Transactions on Image Processing, 2020.pdf

· Q. Luo, X. Fang, Li Liu, C. Yang, Y. Sun, Automated Visual Defect Detection for Flat Steel Surface: A Survey, IEEE Transactions on Instrumentation and Measurement, 2020.pdf

· M. Tavakoliana, M. Lopezb, Li Liu, Selfsupervised pain intensity estimation from facial videos via statistical spatiotemporal distillation, Pattern Reconition Letters, 2020.pdf

· Q. Luo, X. Fang, J. Su, J. Zhou, B. Zhou, C. Yang, Li Liu, W. Gui, L. Tian, Automated Visual Defect Classification for Flat Steel Surface: A Survey, IEEE Transactions on Instrumentation and Measurement, 2020.pdf

· J. Cai, H. Han, J. Cui, J. Chen, Li Liu, S. Zhou, Semisupervised Natural Face Deocclusion, IEEE Transactions on Information Forensics and Security, 2020.pdf

· L. Zhang, C. Zhang, H. Xiao, S. Quan, G. Kuang, Li Liu, A Class Imbalance Loss for Imbalanced Object Recognition, IEEE Journal of Selected Topics in Applied Earth Observations and Remote, 2020pdf

Publications in 2019

· Li Liu, J. Chen, P. Fieguth, G. Zhao, M. Pietikäinen, R. Chellappa, From BoW to CNN: Two Decades of Texture Representation for Texture Classification, International Journal of Computer Vision, vol. 127, pp. 74-109, 2019.pdf

· Li Liu, M. Pietikäinen, J. Chen, G. Zhao, X. Wang, R. Chellappa, Guest Editors’ Introduction to the Special Section on Compact and Efficient Feature Representation and Learning in Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 10, 2019.pdf

· Li Liu, J. Chen, G. Zhao, P. Fieguth, X. Chen, M. Pietikäinen, Texture Classification in Extreme Scale Variations using GANet, IEEE Transactions on Image Processing, vol. 28, pp. 3910-3922, 2019.pdf

· X. Liu, L. Wang, X. Zhu, M. Li, E. Zhu, T. Liu, Li Liu, Y. Dou, J. Yin, Absent Multiple Kernel Learning Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.pdf

· J. Wu, W. Zhuge, X. Liu, Li Liu, C. Hou, Fragmentary Multiinstance Classification, IEEE Transactions on Cybernetics, 2019.pdf

· X. Zhao, Y. Lin, Li Liu, J. Heikkilä, W. Zheng, Dynamic Texture Classification Using Unsupervised 3D Filter Learning and Local Binary Encoding. IEEE Transactions on Multimedia, vol. 21, no.7, pp. 1694-1708, 2019.pdf

· Q. Ling, Y. Guo, Z. Lin, Li Liu, W. An, A Constrained Sparse Representation Based Binary Hypothesis Model for Target Detection in Hyperspectral Imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, pp. 1933-1947, 2019.pdf

· Y. Liu, Y. Guo, Li Liu, E. Bakkera, M. Lew, CycleMatch: A Cycle consistent Embedding Network for Image-Text Matching, Pattern Recognition, vol. 93, pp. 365-379, 2019.pdf

· Y. Liu, W. Chen, Li Liu, M.S. Lew, SwapGAN: A Multistage Generative Approach for Person to Person Fashion Style Transfer, IEEE Transactions on MultiMedia, vol. 21, no. 9, 2019.pdf

Published earlier

· Y. Liu, Li Liu, Y. Guo, M. Lew, Learning Visual and Textual Representations for Multimodal Matching and Classification, Pattern Recognition, vol, 84, pp. 51-67, 2018.pdf

· Li Liu, P. Fieguth, Y. Guo, X. Wang, M. Pietikäinen, Local Binary Features for Texture Classification: Taxonomy and Experimental Study, Pattern Recognition, vol. 62, pp. 135-160, 2017.pdf

· J. Chen, V. Patel, Li Liu, V. Kellokumpu, G. Zhao, M. Pietikäinen, R. Chellappa, Robust Local Feature for Remote Face Recognition, Image and Vision Computing, vol. 64, pp. 34-46, 2017.pdf

· Li Liu, S. Lao, P. Fieguth, Y. Guo, X. Wang, M. Pietikäinen, Median Robust Extended Local Binary Pattern for Texture Classification, IEEE Transactions on Image Processing, vol. 25, no. 3, pp. 1368-1381, 2016.pdf

· Li Liu, P. Fieguth, G. Zhao, M. Pietikäinen, D. Hu, Extended Local Binary Patterns for Face Recognition, Information Sciences, vol. 358-359, no. 1, pp. 56-72, 2016.pdf

· Li Liu, L. Wang, L. Zhao, P. Fieguth, Random Projections and Single BoW for Fast and Robust Texture Segmentation, Information Sciences, vol. 370-371, no. 20, pp. 428-445, 2016.pdf

· Y. Guo, Y. Lei, Li Liu, Y. Wang, M. Bennamoune, Ferdous Sohel, EI3D: Expression Invariant 3D Face Recognition based on Feature and Shape Matching, Pattern Recognition Letters, vol. 83, pp. 403-412, 2016. (JUFO Ranking: 2)pdf

· Li Liu, Y. Wei, P. Fieguth, G. Kuang, Fusing Sorted Random Projections for Robust Texture Classification and Material Categorization, IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 3, pp. 482-496, 2015.pdf

· Y. Xie, X. Zhang, X. Luan, Li Liu, X. Zhang, A novel specific image scenes detection method, Multimedia Tools and Applications, vol. 74. no. 1, 105-122, 2015.pdf

· Li Liu, Y. Long, P. Fieguth, S. Lao, G. Zhao, BRINT: Binary Rotation Invariant and Noise Tolerant Texture Classification, IEEE Transactions on Image Processing, vol. 23, no. 7, pp. 3071-3084, 2014.pdf

· Li Liu, Y. Xie, Y. Wei, S. Lao, Survey of Local Binary Pattern based Approach, Journal of Image and Graphica, vol. 19, no. 12, 2014. (In Chinese).

· Li Liu and P. Fieguth, Texture Classification from Random Features, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 3, pp. 574-586, 2012.pdf

· Li Liu, P. Fieguth, D. Clausi, G. Kuang, Sorted Random Projections for Robust Rotation Invariant Texture Classification, Pattern Recognition, vol. 45, no. 6, pp. 2405-2418, 2012.pdf

· N. Wang, G. Shi, Li Liu, L. Zhao, G. Kuang, Polarimetric SAR Target Detection Using the Reection Symmetry, IEEE Geoscience and Remote Sensing Letters, vol. 9, no. 6, pp. 1104-1108, 2012.pdf

· Li Liu, L. Zhao, Y. Long, G. Kuang, P. Fieguth, Extended Local Binary Patterns for Texture Classification, Image and Vision Computing, vol. 30, no. 2, pp. 80-99, 2012. (JUFO Ranking: 2)pdf

· G. Gao, Li Liu, L. Zhao, G. Shi, G. Kuang, An Adaptive and Fast CFAR Algorithm based on Automatic Censoring for Target Detection in High-Resolution SAR Images, IEEE Transactions on Geoscience Remote Sensing, vol. 47, no. 6, pp. 1685-1697, 2009.pdf

· Li Liu, G. Kuang, Survey of Image Texture Feature Extraction Methods, Journal of Image and Graphica, vol. 14, no. 3, 2009.pdf

2 Conference Proceedings

· H Xu, SH Zhi, L Liu, Cross Domain Few Shot Classification via Inter-Source Stylization, International Conference on Image Processing (ICIP), 2023.

· J Chen, W Deng, B Peng, T Liu, Y Wei, L Liu, Variational Information Bottleneck for Cross Domain Object Detection, ICME, 2023.

· X Ying, L Liu, Y Wang, R Li, N Chen, Z Lin, W Sheng, S Zhou, Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection with Single Point Supervision, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023.

· S Sun, S Zhi, J Heikkilä, L Liu, Evidential Uncertainty and Diversity Guided Active Learning for Scene Graph Generation, International Conference on Learning Representations (ICLR), 2023.

· Z Su, M Pietikainen, L Liu, From Local Binary Patterns to Pixel Difference Networks for Efficient Visual Representation Learning, the Scandinavian Conference on Image Analysis (SCIA), 2023.

· J Mustaniemi, J Kannala, E Rahtu, L Liu, J Heikkilä, BS3D: Building-scale 3D Reconstruction from RGB-D Images, the Scandinavian Conference on Image Analysis (SCIA), 2023.

· Z Su, M Welling, M Pietikäinen, L Liu, SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation, International Conference on 3D Vision, 2022.

· G Zhu, R Wang, C Han, Y Liu, Y Ding, M Liu, L Liu, N Sang, RFNet: A Refinement Network for Semantic Segmentation, ICPR, 2022.

· X Zhang, C Zhang, J Sui, C Sheng, W Deng, L Liu, Boosting lip reading with a multiview fusion network, ICME, 2022.

· S Wang, X Liu, L Liu, W Tu, X Zhu, J Liu, S Zhou, E Zhu, Highly efficient Incomplete Large scale Multiview Clustering with Consensus Bipartite Graph, International Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

· L Wang, X Dong, Y Wang, L Liu, W An, Y Guo, Learnable Lookup Table for Neural Network Quantization, International Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

· K Li, L Wang, L Liu, Q Ran, K Xu, Y Guo, Decoupling Makes Weakly Supervised Local Feature Better, International Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

· J Zhang, Z Su, Y Feng, X Lu, M Pietikainen, L Liu, Dynamic Binary Neural Network by Learning Channel-wise Thresholds, ICASSP, 2022.

· J Liu, X Liu, Y Yang,L Liu, S Wang, W Liang, J Shi,One-pass Multiview Clustering for Large scale Data,International Conference on Computer Vision (ICCV), 2021.

· X Liu, S Zhou,L Liu, C Tang, S Wang, J Liu, Y Zhang,Localized Simple Multiple Kernel kmeans, International Conference on Computer Vision (ICCV), 2021.

· Z Su, W Liu, Z Yu, D Hu, Q Liao, Q Tian, M Pietikäinen,L Liu,Pixel Difference Networks for Efficient Edge Detection, International Conference on Computer Vision (ICCV, Oral Presentation), 2021.

Glad to let you know that the camera-ready paper is uploaded in the CMT system.Also the arXiv paper can be seen in https://arxiv.org/abs/2108.07009, the code is released in github: https://github.com/zhuoinoulu/pidinet.

· C Sheng, M Pietikäinen, Q Tian,L Liu,Cross-modal SelfSupervised Learning for Lip Reading: When Contrastive Learning meets Adversarial Training,ACM International Conference on Multimedia, 2021.

· W Deng, Y Cui, Z Liu, G Kuang, D Hu, M Pietikäinen,L Liu,Informative Class Conditioned Feature Alignment for Unsupervised Domain Adaptation,ACM International Conference on Multimedia, 2021.

· L Zhao, W Deng, G Kuang, D Hu,L Liu,Transferable Discriminative Feature Mining for Unsupervised Domain Adaptation,International Conference on Image Processing, 2021.

· Y Cui, W Xiong, M Tavakolian,L Liu, SemiSupervised Few Shot Class Incremental Learning, International Conference on Image Processing, 2021.

· X Liu,L Liu, S Wang, Q Liao, W Tu, C Tang, J Liu, Y Zhang, E Zhu, One Pass Late Fusion Multiview Clustering, International Conference on Machine Learning (ICML), 2021.

· L. Fang, X. Liu, Li Liu, H. Xu, W. Kang, JGR P2O: Joint Graph Reasoning based Pixel to Offset Prediction Network for 3D Hand Pose Estimation from a Single Depth Image, European Conference on Computer Vision (ECCV), 2020.pdf

· Z. Su, L. Fang, W. Kang, D. Hu, M Pietikäinen, Li Liu, Dynamic Group Convolution for Accelerating Convolutional Neural Networks, European Conference on Computer Vision (ECCV), 2020.pdf

· Z. Su, M. Pietikäinen, Li Liu, BIRD: Learning Binary and Illumination Robust Descriptor for Face Recognition, The British Machine Vision Conference (BMVC), 2019.pdf

· J. Sui, Z. Liu, Li Liu., A. Jung, T. Liu, B. Peng, X. Li, Sparse Subspace Clustering for Evolving Data Streams, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7455-7459, 2019.pdf

· X. Zhao, Y. Lin, Li Liu, Dynamic Texture Recognition Using 3D Random Features, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2102-2106, 2019.pdf

· X. Zhu, X. Liu, M. Li, E. Zhu, Li Liu, Z. Cai, J. Yin, W. Gao, Localized Incomplete Multiple Kernel kmeans, International Joint Conference on Artificial Intelligence (IJCAI), 2018.pdf

· N. Liu, B. Zhang, Y. Zong, Li Liu, J. Chen, G. Zhao, J. Zhu, Super Wide Regression Network for Unsupervised Cross Database Facial Expression Recognition, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.pdf

· N. Liu, Y. Zong, B. Zhang, Li Liu, J. Chen, G. Zhao, J. Zhu, Unsupervised Cross Corpus Speech Emotion Recognition Using Domain Adaptive Subspace Learning, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2018.pdf

· Y. Guo, Y. Liu, M. Boer, Li Liu, M. Lew, A Dual Prediction Network For Image Captioning, IEEE International Conference on Multimedia and Expo (ICME), 2018.pdf

· Xin Zhang, Li Liu, Yuxiang Xie, J. Chen, Lingda Wu and M. Pietikäinen, Rotation Invariant Local Binary Convolution Neural Networks, International Conference on Computer Vision Workshop on Compact and Efficient Feature Representation and Learning in Computer Vision, 2017.

· S. Guo, Li Liu, W. Wang, S. Lao, Liang Wang, An Attention Model Based on Spatial Transformers for Scene Recognition, International Conference on Pattern Recognition, 2016.pdf

· Li Liu, P. Fieguth, X. Wang, M. Pietikäinen, Evaluation of LBP and Deep Texture Descriptors with A New Robustness Benchmark, European Conference on Computer Vision (ECCV), 2016.pdf

· Li Liu, P. Fieguth, M. Pietikäinen and S. Lao, Median Robust Extended Local Binary Pattern for Texture Classification, IEEE International Conference on Image Processing (ICIP), 2015.pdf

· Li Liu, P. Fieguth, G. Zhao and M. Pietikäinen, Extended Local Binary Pattern Fusion for Face Recognition, IEEE International Conference on Image Processing (ICIP), 2014..pdf

· Li Liu, B. Yang, P. Fieguth, Z. Yang and Y. Wei, BRINT: A Binary Rotation Invariant And Noise Tolerant Texture Descriptor, IEEE International Conference on Image Processing (ICIP), 2013.pdf

· Li Liu, P. Fieguth, G. Kuang, H. Zha, Sorted Random Projections for Robust Texture Classification, International Conference on Computer Vision (ICCV), 2011.pdf

· Li Liu, P. Fieguth and G. Kuang, Combining Sorted Random Features for Texture Classification, International Conference on Image Processing (ICIP), 2011.pdf

· Li Liu, P. Fieguth and G. Kuang, Generalized Local Binary Patterns for Texture Classification, British Machine Vision Conference (BMVC), 2011.pdf

· Li Liu, P. Fieguth and G. Kuang, Compressed Sensing for Robust Texture Classification, Asian Conference on Computer Vision (ACCV), 2010, Oral Presentation.pdf

· Li Liu and P. Fieguth, Texture Classification Using Compressed Sensing, Canadian Conference on Computer and Robot Vision (CRV), 2010.pdf