Dr Lingqiao Liu

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• Journals

  Year	Citation
  2019	Zhang, L., Wang, P., Shen, C., Liu, L., Wei, W., Zhang, Y., & van den Hengel, A. (2019). Adaptive Importance Learning for Improving Lightweight Image Super-Resolution Network. International Journal of Computer Vision, 21 pages. DOI
  2019	Wei, X., Wang, P., Liu, L., Shen, C., & Wu, J. (2019). Piecewise Classifier Mappings: Learning Fine-Grained Learners for Novel Categories with Few Examples. IEEE Transactions on Image Processing, 28(12), 6116-6125. DOI
  2019	Wang, P., Liu, L., Shen, C., & Shen, H. (2019). Order-aware convolutional pooling for video based action recognition. Pattern Recognition, 91, 357-365. DOI
  2017	Wang, L., Liu, L., & Zhou, L. (2017). A graph-embedding approach to hierarchical visual word mergence. IEEE Transactions on Neural Networks and Learning Systems, 28(2), 308-320. DOI Scopus1
  2017	Li, Y., Liu, L., Shen, C., & Hengel, A. (2017). Mining Mid-level Visual Patterns with Deep CNN Activations. International Journal of Computer Vision, 121(3), 344-364. DOI Scopus11 WoS8
  2017	Qiao, R., Liu, L., Shen, C., & van den Hengel, A. (2017). Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition. Pattern Recognition, 66, 202-212. DOI Scopus26 WoS18
  2017	Liu, L., Wang, P., Shen, C., Wang, L., van den Hengel, A., Wang, C., & Shen, H. (2017). Compositional model based Fisher vector coding for image classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), 2335-2348. DOI Scopus12 WoS6
  2016	Liu, L., Shen, C., & van den Hengel, A. (2016). Cross-convolutional-layer pooling for image recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(11), 2305-2313. DOI Scopus20 WoS13 Europe PMC2
  2016	Zhou, L., Wang, L., Liu, L., Ogunbona, P., & Shen, D. (2016). Learning discriminative Bayesian networks from high-dimensional continuous neuroimaging data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), 2269-2283. DOI Scopus11
  2016	Liu, L., Wang, L., & Shen, C. (2016). A generalized probabilistic framework for compact codebook creation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), 224-237. DOI Scopus2
  2016	Wang, P., Cao, Y., Shen, C., Liu, L., & Shen, H. (2016). Temporal pyramid pooling based convolutional neural network for action recognition. IEEE Transactions on Circuits and Systems for Video Technology, 27(99), 1-8. DOI Scopus28 WoS19
  2015	Wang, C., Wang, L., & Liu, L. (2015). Density maximization for improving graph matching with its applications. IEEE Transactions on Image Processing, 24(7), 2110-2123. DOI Scopus6
  2014	Wang, L., Zhou, L., Shen, C., Liu, L., & Liu, H. (2014). A hierarchical word-merging algorithm with class separability measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(3), 417-435. DOI Scopus10 WoS6 Europe PMC1
  2013	Liu, X., Yin, J., Wang, L., Liu, L., Liu, J., Hou, C., & Zhang, J. (2013). An adaptive approach to learning optimal neighborhood kernels. IEEE Transactions on Cybernetics, 43(1), 371-384. DOI
  2012	Liu, X., Wang, L., Yin, J., & Liu, L. (2012). Incorporation of radius-info can be simple with SimpleMKL. Neurocomputing, 89, 30-38. DOI
  —	Chen, Y., Shen, C., Chen, H., Wei, X. -S., Liu, L., & Yang, J. (n.d.). Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization.
  —	Qiao, R., Liu, L., Shen, C., & Hengel, A. V. D. (n.d.). Visually Aligned Word Embeddings for Improving Zero-shot Learning.
  —	Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (n.d.). Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation.
  —	Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (n.d.). Structured Binary Neural Networks for Image Recognition.

• Conference Papers

  Year	Citation
  2019	Wei, X., Zhang, C., Liu, L., Shen, C., & Wu, J. (2019). Coarse-to-Fine: A RNN-Based Hierarchical Attention Model for Vehicle Re-identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11362 LNCS (pp. 575-591). Switzerland: Springer. DOI
  2018	Zhuang, B., Shen, C., Tan, M., Liu, L., & Reid, I. (2018). Towards Effective Low-Bitwidth Convolutional Neural Networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 7920-7928). DOI Scopus5
  2018	Milan, A., Pham, T., Vijay, K., Morrison, D., Tow, A., Liu, L., . . . Leitner, J. (2018). Semantic segmentation from limited training data. In 2018 IEEE International Conference on Robotics and Automation (ICRA) Vol. abs/1709.07665 (pp. 1908-1915). Brisbane, Australia: IEEE. DOI Scopus2 WoS1
  2018	Yang, J., Gong, D., Liu, L., & Shi, Q. (2018). Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11207 LNCS (pp. 675-691). Munich. DOI Scopus1
  2017	Chen, Z., Jacobson, A., Sunderhauf, N., Upcroft, B., Liu, L., Shen, C., . . . Milford, M. (2017). Deep Learning Features at Scale for Visual Place Recognition. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 3223-3230). Online. DOI Scopus28
  2017	Chen, Y., Shen, C., Wei, X., Liu, L., & Yang, J. (2017). Adversarial PoseNet: a structure-aware convolutional network for human pose estimation. In Proceedings of the IEEE International Conference on Computer Vision (ICCV 2017) Vol. 2017 (pp. 1221-1230). Piscataway, NJ: IEEE. DOI Scopus43 WoS17
  2017	Zhuang, B., Liu, L., Shen, C., & Reid, I. (2017). Towards context-aware interaction recognition for visual relationship detection. In Proceedings 2017 IEEE International Conference on Computer Vision ICCV 2017 Vol. 2017-October (pp. 589-598). Venice, Italy: IEEE. DOI Scopus13 WoS3
  2017	Wang, P., Liu, L., Shen, C., Huang, Z., van den Hengel, A., & Shen, H. (2017). Multi-attention network for one shot learning. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 6212-6220). Online: IEEE. DOI Scopus14 WoS6
  2017	Gong, D., Yang, J., Liu, L., Zhang, Y., Reid, I., Shen, C., . . . Shi, Q. (2017). From motion blur to motion flow: a deep learning solution for removing heterogeneous motion blur. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 3806-3815). Online: IEEE. DOI Scopus22 WoS4
  2017	Teney, D., Liu, L., & van den Hengel, A. (2017). Graph-structured representations for visual question answering. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 3233-3241). Online: IEEE. DOI Scopus23 WoS5
  2017	Li, Y., Lin, G., Zhuang, B., Liu, L., Shen, C., & van den Hengel, A. (2017). Sequential person recognition in photo albums with a recurrent network. In Proceedings: 30th IEEE Conference on Computer Vision and Pattern Recognition Vol. 2017-January (pp. 5660-5668). Honolulu: IEEE. DOI Scopus9 WoS2
  2017	Zhuang, B., Liu, L., Li, Y., Shen, C., & Reid, I. (2017). Attend in groups: a weakly-supervised deep learning framework for learning from web data. In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) Vol. 2017-January (pp. 2915-2924). Online: IEEE. DOI Scopus8 WoS11
  2017	Shen, T., Lin, G., Liu, L., Shen, C., & Reid, I. (2017). Weakly supervised semantic segmentation based on web image co-segmentation. In British Machine Vision Conference 2017, BMVC 2017. Scopus6
  2016	Ge, Z., McCool, C., Sanderson, C., Wang, P., Liu, L., Reid, I., & Corke, P. (2016). Exploiting temporal information for DCNN-based fine-grained object classification. In A. Liew, B. Lovell, C. Fookes, J. Zhou, Y. Gao, M. Blumenstein, & Z. Wang (Eds.), Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016) (pp. 442-447). Gold Coast, AUSTRALIA: IEEE. DOI Scopus2
  2016	Qiao, R., Liu, L., Shen, C., & van den Hengel, A. (2016). Less is more: zero-shot learning from online textual documents with noise suppression. In Proceedings of the 29th IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 2249-2257). Las Vegas, NV: IEEE. DOI Scopus47 WoS28
  2016	Wu, Q., Shen, C., Liu, L., Dick, A., & Van Den Hengel, A. (2016). What value do explicit high level concepts have in vision to language problems?. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 203-212). Las Vegas, NV: IEEE. DOI Scopus179 WoS83
  2016	Wang, P., Liu, L., Shen, C., Huang, Z., Van Den Hengel, A., & Shen, H. (2016). What's wrong with that object? Identifying images of unusual objects by modelling the detection score distribution. In Proceedings of the 29th IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 1573-1581). Las Vegas, NV: IEEE. DOI Scopus6 WoS3
  2016	Li, Y., Liu, L., Shen, C., & van den Hengel, A. (2016). Image co-localization by mimicking a good detector’s confidence score distribution. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Proceedings of the 14th European Conference on Computer Vision, Part II Vol. 9906 LNCS (pp. 19-34). Amsterdam, Netherlands: Springer International Publishing. DOI Scopus15 WoS11
  2015	Li, Y., Liu, L., Shen, C., & Van Den Hengel, A. (2015). Mid-level deep pattern mining. In Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 971-980). Boston, MA: IEEE. DOI Scopus52 WoS30
  2015	Liu, L., Shen, C., & van den Hengel, A. (2015). The treasure beneath convolutional layers: cross-convolutional-layer pooling for image classification. In Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 4749-4757). Boston, MA: IEEE. DOI Scopus90 WoS48
  2014	Zhou, L., Wang, L., Liu, L., Ogunbona, P., & Shen, D. (2014). Max-margin based learning for discriminative Bayesian network from neuroimaging data. In Proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention Vol. 8675 LNCS (pp. 321-328). Boston, MA, USA: Springer. DOI Scopus2
  2014	Liu, L., Shen, C., Wang, L., Van Den Hengel, A., & Wang, C. (2014). Encoding high dimensional local features by sparse coding based fisher vectors. In Proceedings of the 27th International Conference on Neural Information Processing Systems Vol. 2 (pp. 1143-1151). Online: MIT Press. Scopus49 WoS1
  2014	Wang, C., Wang, L., & Liu, L. (2014). Progressive mode-seeking on graphs for sparse feature matching. In Proceedings of the 13th European Conference on Computer Vision Vol. 8690 LNCS (pp. 788-802). Zurich, Switzerland: Springer. DOI Scopus18
  2013	Wang, C., Wang, L., & Liu, L. (2013). Improving graph matching via density maximization. In 2013 IEEE International Conference on Computer Vision (ICCV) (pp. 3424-3431). USA: IEEE. DOI
  2013	Liu, L., & Wang, L. (2013). A scalable unsupervised feature merging approach to efficient dimensionality reduction of high-dimensional visual data. In 2013 IEEE International Conference on Computer Vision (ICCV) (pp. 3008-3015). USA: IEEE. DOI
  2013	Zhang, J., Wang, L., Liu, L., Zhou, L., & Li, W. (2013). Accelerating the divisive information-theoretic clustering of visual words. In 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) (pp. 1-8). USA: IEEE. DOI
  2013	Zhou, L., Wang, L., Liu, L., Ogunbona, P., & Shen, D. (2013). Discriminative brain effective connectivity analysis for Alzheimer's disease: a kernel learning approach upon sparse Gaussian Bayesian network. In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2243-2250). USA: IEEE. DOI
  2012	Liu, L., & Wang, L. (2012). What has my classifier learned? Visualizing the classification rules of bag-of-feature model by support region detection. In 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 3586-3593). USA: IEEE. DOI
  2011	Liu, L., & Wang, L. (2011). Exploring latent class information for image retrieval using the Bag-of-Feature model. In Proceedings of the 19th ACM international conference on Multimedia (pp. 1405-1408). New York; USA: ACM. DOI
  2011	Liu, L., Wang, L., & Liu, X. (2011). In defense of soft-assignment coding. In 2011 IEEE International Conference on Computer Vision (ICCV) (pp. 2486-2493). USA: IEEE. DOI
  2011	Liu, L., Wang, L., & Shen, C. (2011). A generalized probabilistic framework for compact codebook creation. In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (pp. 1537-1544). USA: IEEE. DOI Scopus9

Introduction to Statistic Machine Learning, Puzzle based Learning, Big Data Analysis and Project, Artificial Intelligence

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• Current Higher Degree by Research Supervision (University of Adelaide)

  Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
  2019	Principal Supervisor	Deep Generative Models for Structured Data	Doctor of Philosophy	Doctorate	Full Time	Mr James Austin Kortman
  2019	Co-Supervisor	Machine Learning and Natural Language Processing in Stock Prediction	Doctor of Philosophy	Doctorate	Full Time	Mr Jinan Zou
  2018	Principal Supervisor	Semi-Supervised Learning in Deep Learning	Doctor of Philosophy	Doctorate	Full Time	Mr Hai-Ming Xu
  2018	Co-Supervisor	Machine Learning and Strategic Reasoning in Financial Market	Doctor of Philosophy	Doctorate	Full Time	Mr Xiongren Chen
  2018	Co-Supervisor	Large scale simultaneous localization and mapping in real time	Doctor of Philosophy	Doctorate	Full Time	Mr Yu Liu
  2017	Co-Supervisor	Text detection and Recognition in the wild	Doctor of Philosophy	Doctorate	Full Time	Mr Tong He
  2017	Co-Supervisor	Deep Learning and Probabilistic Graphical Models	Doctor of Philosophy	Doctorate	Full Time	Mr Jie Yang

• Past Higher Degree by Research Supervision (University of Adelaide)

  Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
  2018 - 2019	Co-Supervisor	High-performance Object Detection and Tracking using Deep Learning	Master of Philosophy	Master	Full Time	Mr Xinyu Wang
  2017 - 2019	Co-Supervisor	Context Learning and Weakly Supervised Learning for Semantic Segmentation	Doctor of Philosophy	Doctorate	Full Time	Mr Tong Shen
  2014 - 2018	Co-Supervisor	Mid-level Representations for Action Recognition and Zero-shot Learning	Doctor of Philosophy	Doctorate	Full Time	Mr Ruizhi Qiao
  2014 - 2018	Co-Supervisor	Deep Learning Based RGB-D Vision Tasks	Doctor of Philosophy	Doctorate	Full Time	Mr Yuanzhouhan Cao

• Position: Senior Lecturer
• Phone: 83132133
• Email: lingqiao.liu@adelaide.edu.au
• Fax: 8313 4366
• Campus: North Terrace
• Building: Ingkarni Wardli, floor 5
• Room: 5 48b
• Org Unit: School of Computer Science