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 July 2015 to June 2023, 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.
高飞 ，西安电子科技大学杭州研究院，副研究员（湘湖菁英教授）。2015年于西安电子科技大学获得信息与通信工程专业博士学位（导师：高新波 教授）；期间，于澳大利亚悉尼科技大学进行博士联合培养1年（导师：陶大程 教授）。曾任职于杭州电子科技大学计算机学院、浙江省北大信息技术高等研究院。主要研究兴趣包括视觉质量感知、智能内容生成（AIGC）、图像语义分析、绘画机器人、医疗影像分析、工业异常检测等课题。发表IEEE TNNLS、TCyber、TIP、CVPR、ICCV、ACM MM、AAAI、IJCAI、ICRA、IROS等期刊/会议论文30余篇，ESI高被引论文1篇。获得陕西省科学技术奖一等奖、IEEE ICME’21最佳展示奖亚军、全国博士后创新创业大赛铜奖等。主持国家自然科学基金面上项目、青年项目及浙江省自然科学基金青年项目，并参与多项科研课题。目前担任浙江省抗癌协会人工智能肿瘤诊疗专委会委员，及IEEE TIP, TMM, CVPR, ICCV等国际期刊和会议的审稿人。
[Github] [Google Scholar] [DBLP] [课程 Courses]
Fei Gao, Ying Zhou, Ziyun Li, Wenwang Han, Jiaqi Shi, Maoying Qiao, Jinlan Xu, Nannan Wang*. QuARF: Quality-Adaptive Receptive Fields for Degraded Image Perception. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), Accepted, Feb. 25 – Mar. 4, 2025, Philadelphia, Pennsylvania, USA, 2025. [Paper] ~ [Github]
Mingjin Zhang, Wenteng Shang, Fei Gao *, Qiming Zhang, FengQin Lu, Jing Zhang, Semi-supervised Infrared Small Target Detection with Thermodynamic-Inspired Uneven Perturbation and Confidence Adaptation. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), Accepted, 2025. （通信作者）
Mingjin Zhang, Yuanjun Ouyang, Fei Gao, Jie Guo, Qiming Zhang*, Jing Zhang, MOCID: Motion Context and Displacement Information Learning for Moving Infrared Small Target Detection. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), Accepted, 2025.
Mingjin Zhang, Xiaolong Li, Fei Gao, Jie Guo, IRMamba: Pixel Difference Mamba with Layer Restoration for Infrared Small Target Detection. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), Accepted, 2025.
Yuxin Fei, Jinlan Xu, Maoying Qiao, Fei Gao*, MAJoR: Visual Emotion Analysis via Multi-Attribute Joint Reasoning, ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Accepted, 2025. [Github]
Fei Gao, Yuhao Lin, Jiaqi Shi, Maoying Qiao, Nannan Wang*. AesMamba: Universal Image Aesthetic Assessment with State Space Models. The 32nd ACM Multimedia Conference (ACM MM), 7444-7453, 2024 (Oral). Paper@OpenReview ~ Paper@ACMMM ~ [Github]
Yu Chen *, Fei Gao *, Yanguang Zhang, Maoying Qiao, Nannan Wang. **Generating Handwritten Mathematical Expressions From Symbol Graphs: An End-to-End Pipeline. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 15675-15685, Seattle WA, USA, June 17-21, 2024. (* Equal Contributions) [Paper] ~ [Github]
Renshu Gu, Jiajun Zhu, Yixuan Si, Fei Gao, Jiamin Xu, Gang Xu, 3D Human Pose Estimation from Multiple Dynamic Views via Single-view Pretraining with Procrustes Alignment, Proceedings of the 32nd ACM International Conference on Multimedia, 10363-10372, 2024.
Fan Gong, Jialiang Chen, Jiajun Zhu, Qijian Bao, Fei Gao, Renshu Gu, Gang Xu, Micro-Action Recognition via Hierarchical Fusion and Inference, 微动作识别挑战赛 Micro-Action Recognition Challenge 全球第四名, Proceedings of the 32nd ACM International Conference on Multimedia, 11327-11332, 2024.
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. Paper ~ [Github]
Fei Gao, Lingna Dai, Jingjie Zhu, Mei Du, Yiyuan Zhang, Maoying Qiao, Chenghao Xia, Nannan Wang, and Peng Li *， Human-Robot Interactive Creation of Artistic Portrait Drawings, 2024 IEEE International Conference on Robotics and Automation (ICRA), 11297-11304, May13-17, 2024, Yokohama, Japan. (* Corresponding Author) Paper ~ 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.