Biography

Fei Gao is currently with the Intelligent Information Processing (IIP) Lab. and Hangzhou Institute of Technology, at Xidian University. He received his Bachelor Degree in Electronic Engineering and Ph.D. Degree in Information and Communication Engineering from Xidian University (Xi'an, China) in 2009 and 2015, respectively. From Oct. 2012 to Sep. 2013, he was a Visiting Ph.D. Candidate in University of Technology, Sydney (UTS) in Australia. From 2015 to 2022, he works at Hangzhou Dianzi University.

He mainly applies machine learning techniques to computer vision problems. His research interests include visual quality assessment and enhancement, intelligent visual arts generation, biomedical image analysis, etc. His research results have expounded in more than 30 publications at prestigious journals and conferences. He serverd for a number of journals and conferences.

[Github] [Google Scholar] [DBLP] [CN]

Selected Publications

• Fei Gao, Yifan Zhu, Chang Jiang, Nannan Wang, Human-Inspired Facial Sketch Synthesis with Dynamic Adaptation, Proceedings of the International Conference on Computer Vision (ICCV), 7237-7247, 2023. [Github]

• Biao Ma, Fei Gao* , Chang Jiang, Nannan Wang, Gang Xu, "Semantic-aware Generation of Multi-view Portrait Drawings," the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 1258-1266, 2023. [paper_arxiv] ~ [Github] ~ [project]

• Chang Jiang, Fei Gao*, Biao Ma, Yuhao Lin, Nannan Wang, Gang Xu, "Masked and Adaptive Transformer for Exemplar Based Image Translation," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp. 22418-22427. [paper_cvpr] ~ [paper_arxiv] ~ [project]

• Fei Gao, Xingxin Xu, Jun Yu, Meimei Shang, Xiang Li, and Dacheng Tao, "Complementary, Heterogeneous and Adversarial Networks for Image-to-Image Translation," IEEE Transactions on Image Processing, vol. 30, pp. 3487 - 3498, 2021. [paper_ieee] ~ [project]

• Jun Yu, Xingxin Xu, Fei Gao*, Shengjie Shi, et al. "Towards Realistic Face Photo-Sketch Synthesis via Composition-Aided GANs," IEEE Transactions on Cybernatics, vol. 51, no. 9, pp. 4350 - 4362, 2021. (Corresponding Author) [project] ~ [paper_arxiv] ~ [paper_ieee]

• Hanliang Jiang, Fuhao Shen, Fei Gao*, Weidong Han. Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification. Pattern Recognition, 113: 107825, 2021. [paper@PR] ~ [paper@arxiv] ~ [project] (Corresponding Author)

• Fei Gao, Jingjie Zhu, Zeyuan Yu, Peng Li, Tao Wang, "Making Robots Draw A Vivid Portrait In Two Minutes," in the Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020), pp. 9585-9591, Las Vegas, USA, 2020. [paper_iros] ~ [paper_ariv] ~ [project]

  • AiSketcher: Portrait Drawing Robot. (妙绘艺术微信小程序可试用)

• Lin Zhao, Meimei Shang, Fei Gao*, et al. "Representation Learning of Image Composition for Aesthetic Prediction," Computer Vision and Image Understanding (CVIU), vol. 199, 103024, Oct. 2020. [project]~[paper]

• 黄菲, 高飞, 朱静洁, 戴玲娜, 俞俊. 基于生成对抗网络的异质人脸图像合成: 进展与挑战[J]. 南京信息工程大学学报, 2019, 11(6): 660~681. [paper]

  Fei Huang, Fei Gao, et al. Heterogeneous face synthesis via generative adversarial networks: progresses and challenges. Journal of Nanjing University of Information Science and Technology (Natural Science Edition), 2019, 11(6): 660-681. (In Chinese)

• Fei Gao, Shengjie Shi, et al., "Improving Facial Attractiveness Prediction via Co-attention Learning," 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4045-4049, 12-17 May 2019. [paper]~[project]

• Fei Gao, Jun Yu, Suguo Zhu, Qingming Huang, Qi Tian, "Blind Image Quality Prediction by Exploiting Multi-level Deep Representations," Pattern Recognition, vol 81, pp. 432-442, Sep. 2018. [paper]

• Fei Gao, Yi Wang, Panpeng Li, et al., "DeepSim: Deep similarity for image quality assessment," Neurocomputing, vol. 157, pp. 104-114, 2017. [paper]~[project]

• Fei Gao and Jun Yu, "Biologically inspired image quality assessment," Signal Processing, vol. 124, pp. 210-219, 2016. [paper] ~ [project]

• Fei Gao, Dacheng Tao, Xinbo Gao, and Xuelong Li, "Learning to rank for blind image quality assessment," IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 10, pp. 2275-2290, Oct. 2015.

• Xinbo Gao, Fei Gao, Dacheng Tao, and Xuelong Li, "Universal blind image quality assessment metrics via natural scene statistics and multiple kernel learning," IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 12, pp. 2013-2026, 2013.