Lingyu Liang Associate Professor School of Electronic and Information Engineering South China University of Technology Guangzhou, China Email: lianglysky at gmail dot com

Biography

I am currently an associate professor at South China University of Technology (SCUT). My research interests include image analysis and recognition, machine learning and computational photography. Specifically, I focus on 1) Multi-task image analysis, recognition and editing, covering images of face, natural scene, document/text and architectural design; 2) Models of high dimentional data representation, learning and inference, like GNN, PDE learning and sparse coding.

I got my B.Eng. and Ph.D. in School of Electronic and Information Engineering, SCUT, supervised by Prof. Lianwen Jin, in 2009 and 2014, respectively. From 2014 to 2016, I was a post-doctoral fellow in School of Computer Science and Engineering, SCUT, with Prof. Yong Xu. From 2016 to 2017, I was an honorary post-doctoral fellow in Computer Science and Engineering Department, The Chinese University of Hong Kong, with Prof. Jiaya Jia.

Selected Publications [Google Scholar] [DBLP]

# indicates equal contribution
* indicates corresponding auther

• PDE Learning of Filtering and Propagation for Task-Aware Facial Intrinsic Image Analysis,
  Lingyu Liang, Lianwen Jin, and Yong Xu
  IEEE Transactions on Cybernetics (TCYB), 2022
• Regression Guided by Relative Ranking Using Convolutional Neural Network (R3CNN) for Facial Beauty Prediction,
  Luojun Lin#, Lingyu Liang# and Lianwen Jin.
  IEEE Transactions on Affective Computing (TAFFC), 2022

  [Project]

• Fourier Contour Embedding for Arbitrary-Shaped Text Detection,
  Yiqin Zhu, Jianyong Chen, Lingyu Liang*, Zhanghui Kuang∗, Lianwen Jin, Wayne Zhang
  IEEE CVPR, 2021

  [Project]

• SCUT-HCCDoc: A New Benchmark Dataset of Handwritten Chinese Text in Unconstrained Camera-captured Documents,
  Hesuo Zhang, Lingyu Liang* and Lianwen Jin.
  Pattern Recognition (PR), 2020

  [Project]

• SCUT-AutoALP: A Diverse Benchmark Dataset for Automatic Architectural Layout Parsing,
  Yubo Liu, Yangting Lai, Jianyong Chen, Lingyu Liang*, and Qiaoming Deng.
  IEICE Transactions on Information and Systems , 2020

  [Project]

• Adaptive Label Propagation for Facial Appearance Transfer,
  Lingyu Liang, and Xinglin Zhang.
  IEEE Transactions on Multimedia (TMM), vol.21, no.12, pp.3068-3082, 2019
• Adaptive GNN for Image Analysis and Editing,
  Lingyu Liang, Lianwen Jin and Yong Xu.
  Conference on Neural Information Processing Systems (NeurIPS), 2019
• Attribute-Aware Convolutional Neural Network for Facial Beauty Prediction,
  Luojun Lin, Lingyu Liang, Lianwen Jin and Weijie Chen.
  International Joint Conference on Artificial Intelligence (IJCAI), 2019
  
• Privacy-Preserving Incentive Mechanisms for Mobile Crowdsensing,
  Xinglin Zhang, Lingyu Liang*, Chengwen Luo and Long Cheng.
  IEEE Pervasive Computing, vol.17, no.3, pp.47-57, 2018
  
• SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction,
  Lingyu Liang, Luojun Lin, Lianwen Jin, Duorui Xie and Mengru Li.
  International Conference on Pattern Recognition (ICPR), 2018
  

  [Project]

• Edge-Aware Label Propagation for Mobile Facial Enhancement on the Cloud,
  Lingyu Liang, Lianwen Jin and Deng Liu.
  IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol.27, no.1, pp.125-138, 2017
  
• Region-Aware Scattering Convolution Networks for Facial Beauty Prediction,
  Lingyu Liang, Duorui Xie, Lianwen Jin et al.
  IEEE International Conference on Image Processing (IEEE ICIP), 2017
  
• SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception,
  Duorui Xie, Lingyu Liang, Lianwen Jin et al.
  IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), 2015
• Multiple Facial Image Editing Using Edge-Aware PDE Learning,
  Lingyu Liang, Lianwen Jin, Xin Zhang and Yong Xu.
  Computer Graphics Forum (CGF), vol.34, no.7, pp.203-212, 2015
• Facial Skin Beautification Using Adaptive Region-Aware Masks,
  Lingyu Liang, Lianwen Jin, and Xuelong Li.
  IEEE Transactions on Cybernetics (TCYB), vol.44, no.12, pp.2600-2612, 2014

Teaching

2017-Present	Fall	Deep Learning (Master's Degree Course)
2016-2017	Fall	Machine Learning (Master's Degree Course)
2019-Present	Spring	Deep Learning (Undergraduate Course)
2017-Present	Spring	Data Structure (Undergraduate Course)