Name: Fu Ying
Discipline: Computer Science and Technology
Title: Professor
Contact number:
E-mail: fuying@bit.edu.cn
Address: School of Computer Science, Beijing Institute of Technology Personal Information
Fu Ying, Professor, doctoral supervisor. He received a bachelor's degree in Electronic Information Engineering from Xidian University in 2009, a master's degree in automation from Tsinghua University in 2012, and a Doctor's degree in Information Science and technology from the University of Tokyo in 2015. He worked as a postdoctoral researcher at the University of Tokyo from 2015 to 2016, joined the School of Computer Science, Beijing Institute of Technology in 2016, and was selected as a national high-level talent program in 2017. He has published many papers in international journals such as IEEE TPAMI, IJCV, TIP and international conferences such as ICCV, CVPR, ICML and won the Best Paper Award of ICML2020 and PRCV2019.
One doctoral student and 2-3 master students are enrolled each year. Students who are interested in computational photography, computer vision, machine learning, multimedia image and video analysis and other related fields are welcome to join the research group. Long-term postdoc recruitment, welcome students with optical, computational photography, computer vision, machine learning, multimedia image and video analysis background to join.
Personal Homepage: https://ying-fu.github.io/

Research Direction
Computational photography, Computer vision, Machine learning, Multimedia image and Video analysis, etc.

Personal Information
Fu Ying, Professor, doctoral supervisor. He received a bachelor's degree in Electronic Information Engineering from Xidian University in 2009, a master's degree in automation from Tsinghua University in 2012, and a Doctor's degree in Information Science and technology from the University of Tokyo in 2015. He worked as a postdoctoral researcher at the University of Tokyo from 2015 to 2016, joined the School of Computer Science, Beijing Institute of Technology in 2016, and was selected as a national high-level talent program in 2017. He has published many papers in international journals such as IEEE TPAMI, IJCV, TIP and international conferences such as ICCV, CVPR, ICML and won the Best Paper Award of ICML2020 and PRCV2019.
One doctoral student and 2-3 master students are enrolled each year. Students who are interested in computational photography, computer vision, machine learning, multimedia image and video analysis and other related fields are welcome to join the research group. Long-term postdoc recruitment, welcome students with optical, computational photography, computer vision, machine learning, multimedia image and video analysis background to join.
Personal Homepage: https://ying-fu.github.io/

Personal Information
Fu Ying, Professor, doctoral supervisor. He received a bachelor's degree in Electronic Information Engineering from Xidian University in 2009, a master's degree in automation from Tsinghua University in 2012, and a Doctor's degree in Information Science and technology from the University of Tokyo in 2015. He worked as a postdoctoral researcher at the University of Tokyo from 2015 to 2016, joined the School of Computer Science, Beijing Institute of Technology in 2016, and was selected as a national high-level talent program in 2017. He has published many papers in international journals such as IEEE TPAMI, IJCV, TIP and international conferences such as ICCV, CVPR, ICML and won the Best Paper Award of ICML2020 and PRCV2019.
One doctoral student and 2-3 master students are enrolled each year. Students who are interested in computational photography, computer vision, machine learning, multimedia image and video analysis and other related fields are welcome to join the research group. Long-term postdoc recruitment, welcome students with optical, computational photography, computer vision, machine learning, multimedia image and video analysis background to join.
Personal Homepage: https://ying-fu.github.io/

代表性学术成果
1.Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu*, Carola-Bibiane Schnlieb, Hua Huang. Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems. International Conference on Machine Learning (ICML), Vienna, Austria, 2020. (CCF-A类会议，最佳论文奖，接受率0.04%)
2. Ying Fu, Tao Zhang, Yinqiang Zheng, Debing Zhang, Hua Huang*. Joint Camera Spectral Response Selection and Hyperspectral Image Recovery. IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), 2020. (CCF-A类期刊，IF="17.861)
3. Kaixuan Wei, Ying Fu*, Hua Huang. 3-D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020. (CCF-B类期刊, IF="8.793 )
4. Kaixuan Wei, Ying Fu*, Jiaolong Yang, Hua Huang. A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA,2020. (CCF-A类会议，口头报告，接收率5%)
5. Lizhi Wang, Chen Sun, Maoqing Zhang, Ying Fu, Hua Huang*. DNU: Deep Non-local Unrolling for Computational Spectral Imaging, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA,2020. (CCF-A类会议)
6. Yixi Xiang, Ying Fu*, Lei Zhang, Hua Huang. An Effective Network With ConvLSTM for Low-Light Image Enhancemen, The 2nd Chinese Conference on Pattern Recognition and Computer Vision (PRCV), Xi'an, China, 2019. (最佳论文奖)
7. Lizhi Wang, Tao Zhang, Ying Fu*, Hua Huang. HyperReconNet: Joint Coded Aperture Optimization and Image Reconstruction for Compressive Hyperspectral Imaging, IEEE Transactions on Image Processing (TIP), 2019,28(5): 2257-2270 (CCF-A类期刊，IF="9.34)
8. Ye Xiang, Ying Fu*, Hua Huang. Global Topology Constraint Network for Fine-Grained Vehicle Recognition, IEEE Transactions on Intelligent Transportation Systems (TITS), 2019 (CCF-B类期刊，IF="6.319)
9. Tao Zhang, Ying Fu*, Lizhi Wang, Hua Huang. Hyperspectral Image Reconstruction using Deep External and Internal Learning, IEEE International Conference on Computer Vision (ICCV), Seoul , 2019. (CCF-A类会议)
10. Ye Xiang, Ying Fu*, Pan Ji, Hua Huang. Incremental Learning Using Conditional Adversarial Networks, IEEE International Conference on Computer Vision (ICCV), Seoul , 2019. (CCF-A类会议)
11. Shipeng Zhang, Lizhi Wang*, Ying Fu, Xiaoming Zhong, Hua Huang. Computational Hyperspectral Imaging Based on Dimension-discriminative Low-rank Tensor Recovery, IEEE International Conference on Computer Vision (ICCV), Seoul, 2019. (CCF-A类会议)
12.Kaixuan Wei, Jiaolong Yang, Ying Fu*, David Wipf, Hua Huang. Single Image Reffection Removal Exploiting Misaligned Training Data and Network Enhancements, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, 2019. (CCF-A类会议)
13. Ying Fu, Tao Zhang, Yinqiang Zheng, Debing Zhang, Hua Huang*. Hyperspectral Image Super-Resolution with Optimized RGB Guidance, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, 2019. (CCF-A类会议)
14. Lizhi Wang, Chen Sun, Ying Fu, Min H. Kim, Hua Huang*. Hyperspectral Image Reconstruction Using a Deep Spatial-Spectral Prior, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, 2019. (CCF-A类会议)
15. Ying Fu, Yinqiang Zheng, Hua Huang*, Imari Sato, Yoichi Sato. Hyperspectral Image Super-Resolution With a Mosaic RGB Image, IEEE Transactions on Image Processing (TIP), 2018,27(11): 5539-5552 (CCF-A类期刊，IF="9.34)
16. Ying Fu, Tao Zhang, Yinqiang Zheng, Debing Zhang, Hua Huang*. Joint Camera Spectral Sensitivity Selection and Hyperspectral Image Recovery. European Conference on Computer Vision (ECCV), Munich, Germany, 2018. (CCF-B类会议)
17. Ying Fu, Antony Lam, Imari Sato, and Yoichi Sato. Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Restoration, International Journal of Computer Vision (IJCV), vol. 122, no. 5, pp. 228-245, 2017. (CCF-A类期刊，IF="5.698)
18. Ying Fu, Antony Lam, Imari Sato, Takahiro Okabe, and Yoichi Sato. Reflectance and Fluorescent Spectra Recovery via Actively Lit RGB Images, IEEE Trans. Pattern Analysis and Mahine Intelligence (TPAMI), vol. 38, no. 5, pp. 965-978,2016. (CCF-A类期刊，IF="17.861)
19. Ying Fu, Antony Lam, Imari Sato, Takahiro Okabe, and Yoichi Sato. Separating Reflective and Fluorescent Components using High Frequency Illumination in the Spectral Domain, IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), vol. 38, no. 7, pp. 1313-1326, 2016. (CCF-A类期刊，受邀投稿，IF="17.861)
20. Ying Fu, Yinqiang Zheng, Imari Sato, and Yoichi Sato. Exploiting Spectral-Spatial Correlation for Coded Hyperspectral Image Restoration, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (CCF-A类会议)
21. Ying Fu, Antony Lam, Imari Sato, and Yoichi Sato. Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Denoising, IEEE International Conference on Computer Vision (ICCV), 2015. (CCF-A类会议)
22. Yinqiang Zheng, Ying Fu, Antony Lam, Imari Sato, and Yoichi Sato. Separating Fluorescent and Reflective Components by Using a Single Hyperspectral Image, IEEE International Conference on Computer Vision (ICCV), 2015. (CCF-A类会议)
23. Ying Fu, Antony Lam, Yasuyuki Matsushita, Imari Sato, and Yoichi Sato. Interreflectance Removal Using Fluorescence, European Conference on Computer Vision (ECCV), 2014. (CCF-B类会议)
24. Ying Fu, Antony Lam, Yasuyuki Kobashi, Imari Sato, Takahiro Okabe, and Yoichi Sato. Reflectance and Fluorescent Spectra Recovery based on Fluorescent Chromaticity Invariance under Varying Illumination, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. (CCF-A类会议，口头报告，接收率5.76%)
25. Ying Fu, Antony Lam, Imari Sato, Takahiro Okabe, and Yoichi Sato. Separating Reflective and Fluorescent Components using High Frequency Illumination in the Spectral Domain, IEEE International Conference on Computer Vision (ICCV), 2013. (CCF-A类会议，口头报告，接收率2.52%)
所获奖励