Ying Fu



I am currently a professor with the School of Computer Science and Technology, Beijing Institute of Technology. I received the B.S. degree in Electronic Engineering from Xidian University in 2009, the M.S. degree in Automation from Tsinghua University in 2012, and the Ph.D. degree in information science and technology from the University of Tokyo in 2015. My research interests include computer vision, image and video processing, and computational photography.

CCF Conference Deadlines


Click this link to obtain information about CCF Conference Deadlines.

Recent News


  • [2024.02] Several papers are accepted by IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2024.
  • [2024.02] One paper is accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
  • [2024.01] One paper is accepted by International Conference on Learning Representations (ICLR) 2024.
  • [2023.12] One paper is accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
  • [2023.11] One paper is accepted by Transactions on Geoscience and Remote Sensing (TGRS).

Opening Positions


I’m looking for self-motivated Ph. D./M. S. students with solid background in programming and mathematics. I’m also looking for several PostDocs with strong research background in computer vision, image processing, and deep learning, to join my group.
Please send me email if you have interest.

Selected Publications


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  • RawHDR: High Dynamic Range Image Reconstruction from a Single Raw Image
  • Yunhao Zou, Chenggang Yan, Ying Fu
  • International Conference on Computer Vision (ICCV), 2023
[pdf]  [code&dataset]  [bibtex]

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  • A Large-scale Climate-aware Satellite Image Dataset for Domain Adaptive Land-Cover Semantic Segmentation
  • Songlin Liu*, Linwei Chen*, Li Zhang, Jun Hu, Ying Fu
  • ISPRS Journal of Photogrammetry and Remote Sensing, 2023
[pdf]  [code&dataset]  [bibtex]

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  • Instance Segmentation in the Dark
  • Linwei Chen, Ying Fu, Kaixuan Wei, Dezhi Zheng, Felix Heide
  • International Journal of Computer Vision (IJCV), 2023
[pdf]  [code&dataset]  [bibtex]

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  • ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization
  • Zeqiang Lai*, Kaixuan Wei*, Ying Fu, Philipp Härtel, Felix Heide
  • SIGGRAPH ACM Transactions on Graphics (TOG), 2023
[pdf] [code] [bibtex]

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  • Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
  • Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schnlieb, Hua Huang
  • International Conference on Machine Learning (ICML), 2020 (Oral)
[pdf]  [code]  [bibtex]

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  • A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising
  • Kaixuan Wei, Ying Fu, Jiaolong Yang, Hua Huang
  • IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 (Oral)
[pdf] [code] [bibtex]

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Last Update: Jun. 26, 2020