通讯地址：福建省福州市福州地区大学新区学园路2号 邮编:350108

电子邮箱：xwu@fzu.edu.cn

教育工作经历

2018/09至今， 福州大学机械工程及自动化学院 机电工程系

2012/08-2018/05，北卡罗莱纳州立大学机械工程硕士、博士

2011/08-2012/08，普渡大学 电子与计算机工程 硕士

2007/09-2011/07，电子科技大学 机械电子工程学院 学士

主要教授课程：微机原理与接口技术、数字成像与影像处理

个人简介

吴衔誉，现任福州大学机械工程及自动化学院教授、博士生导师，入选福建省高层次人才（B类）、福州大学旗山学者。2011年获电子科技大学机械电子工程学士学位，2014年获北卡罗来纳州立大学机械工程硕士学位，2018年获该校机械工程博士学位。自2018年9月起任职于福州大学。

长期从事智能计算成像、精密光学测量与神经形态视觉传感等交叉研究，核心方向为新型光学传感与计算成像技术。带领团队融合精密光学仪器、高速成像、计算机视觉与人工智能，突破传统光学成像瓶颈；研制多型自主知识产权精密成像与测量仪器，应用于智能安防、无人机遥感、无损检测与结构健康监测等领域。自主研发的嵌入式光学成像测量系统已规模化部署并商业转化，累计产值超千万元。

作为项目负责人，主持承担国家级重点项目课题及多项部委和省级科研项目。近五年在IEEE TIP、IEEE TCI、Optics Express等国际高水平期刊及ICML等顶级学术会议发表论文四十余篇，授权发明专利二十余项。担任IEEE TCSVT、IEEE TCI、IEEE TIP、EAAI等多个高水平期刊审稿人，IEEE、OPTICA会员，多次受邀在国际学术会议上做邀请报告。

研究方向：

1. 智能计算光学成像与三维重建

2. 视觉检测与智能控制

3. 精密光学成像与测量仪器

4. 神经形态视觉传感与计算

实验室开源资料主页 AOCI Lab： https://xianyuwu123.github.io/ai-lab-website/

【近四年代表性论文】

1. Wang, P., Yu, K., He, H., Huang, F., Wu, X., & Chen, Y. (2026). Mamba-SfP: Toward open-scene 3D shape from polarization via selective state space models. Optics & Laser Technology, 116380. https://doi.org/10.1016/j.optlastec.2026.116380

2. Wang, P., Yu, K., He, H., Huang, F., Wu, X., & Chen, Y. (2026). UD-SfPNet: An underwater descattering shape-from-polarization network for 3D normal reconstruction. Pattern Recognition, 183, 114827. https://doi.org/10.1016/j.patcog.2026.114827

3. Yu K., Wang P., He H., & Wu X.* (2026). Structure-Aware Consistency Priors for Shape from Polarization in Complex Media. Proceedings of the 43rd International Conference on Machine Learning (ICML 2026), Seoul, South Korea, July 2026. (CCF-A类推荐国际顶级会议，Poster Presentation)

4. Zhang X, Wang X, Xu Y, et al. Polarization video frame interpolation for 3D human pose reconstruction with attention mechanism[J]. Optics and Lasers in Engineering, 2025, 193: 109046. (SCI Q1, IF: 3.7)

5. Wu X, Chen J, Li P, et al. (2025). Deep learning-based polarization 3D imaging method for underwater targets. Optics Express, 33(2): 2068-2081. (SCI Q2, IF: 3.3)

6. Wang X, Zhou B, Peng J, et al. (2024). Enhancing three-source cross-modality image fusion with improved DenseNet for infrared polarization and visible light images. Infrared Physics & Technology, 141: 105493. (SCI Q2, IF: 3.4)

7. Wang X, Chen Y, Peng J, et al. (2024). LVTSR: Learning visible image texture network for infrared polarization super-resolution imaging. Optics Express, 32(17): 29078-29098. (SCI Q2, IF: 3.3)

8. Huang F, Wang X, Chen Y, et al. (2024). Bio-inspired foveal super-resolution method for multi-focal-length images based on local gradient constraints. Optics Express, 32(11): 19333-19351. (SCI Q2, IF: 3.3)

9. Huang F, Chen Y, Wang X, et al. (2024). Joint constraints of guided filtering based confidence and nonlocal sparse tensor for color polarization super-resolution imaging. Optics Express, 32(2): 2364-2391. (SCI Q2, IF: 3.3)

10. Wu X, Zhou B, Wang X, et al. (2023). SwinIPISR: A super-resolution method for infrared polarization imaging sensors via swin transformer. IEEE Sensors Journal, 24(1): 468-477. (SCI Q1, IF: 4.5, Top期刊)

11. Huang, F., Chen, Y., Wang, X., Wang, S., & Wu, X. (2023). Spectral Clustering Super-Resolution Imaging Based on Multispectral Camera Array. IEEE Transactions on Image Processing, 32, 1257-1271. (CCF-A类, SCI Q1, IF: 13.7, Top期刊)

12. Huang, F., Cao R., Lin P., Zhou B., Wu, X. (2023). High-Efficiency Multispectral-Polarization Imaging System using Polarization Camera Array with Notch Filters. IEEE Transactions on Instrumentation and Measurement. (SCI Q1, IF: 5.9)

Dr. Xianyu Wu is a Professor and Ph.D. Supervisor at the School of Mechanical Engineering and Automation, Fuzhou University. He is a recipient of the Fujian Province High-Level Talent (Class B) award and the Qishan Scholar award at Fuzhou University. He received his B.E. in Mechatronics Engineering from the University of Electronic Science and Technology of China (UESTC) in 2011, M.S. in Mechanical Engineering from North Carolina State University in 2014, and Ph.D. in Mechanical Engineering from the same institution in 2018. He joined Fuzhou University in September 2018.

His long-term research focuses on the interdisciplinary frontiers of intelligent computational imaging, precision optical measurement, and neuromorphic vision, with a core emphasis on novel optical sensing and computational imaging technologies. As the team leader, he directs a research group dedicated to the deep integration of precision optical imaging and measurement instruments, high-speed optical imaging, computer vision inspection, and artificial intelligence, striving to break through the bottlenecks of traditional optical imaging technologies. He has successfully developed multiple types of precision imaging and measurement instruments with independent intellectual property rights, and his research achievements have been widely applied in fields including intelligent security monitoring, UAV remote sensing imaging, non-destructive material testing, and structural health monitoring.

Dr. Wu serves as a reviewer for multiple high-impact journals including IEEE TCSVT, IEEE TCI, IEEE TIP, and EAAI, and is a member of IEEE and OPTICA. He has been invited to deliver invited talks at international academic conferences on multiple occasions. His current efforts aim to advance the application of artificial intelligence and computational optical imaging in advanced manufacturing, intelligent inspection, medical imaging, and autonomous systems.