Kai-Fu Yang (杨开富)
Associate Research Professor (副研究员)
Computational Vision, Bio-inspired Computer Vision, Medical Image Analysis
视觉认知计算、计算机视觉、医学图像分析

Center for Visual Cognition and Brain-Inspired Computation
University of Electronic Science and Technology of China (UESTC)
No.4, Section 2, North Jianshe Road, Chengdu 610054, China.

Email:yangkf [AT] uestc.edu.cn
[Google Scholar]

About Me

I am an associate research professor at the MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC). I received my Ph.D. degree in Biomedical Engineering from UESTC in 2016 under the supervision of Prof. Yong-Jie Li. From August 2019 to August 2020, I was a visiting scholar at the Computer Vision Lab, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland.

Research Interests

I conduct interdisciplinary research at the intersection of visual cognition and computer vision. My research aims to explore the underlying computational theory of visual cognition and develop bio-inspired methods for computer vision applications. Through a combination of computational modeling and behavioral experiments, such as eye-tracking, we investigate the computational basis of many aspects of vision, such as visual perception, visual attention, and object recognition. In addition, we also try to explore new methods for medical data analysis.

Projects and Publications

(1) Bio-inspired Computer Vision

 

Gray Pixel for Illuminant Estimation

We systematically developed Gray-pixel methods for illuminant estimation. This included advancing the gray-pixel hypothesis, validating it, and developing algorithms for color constancy and image dehazing. We also defined the problem of nighttime color constancy (NCC) and collected the first NCC dataset.
  • KF Yang, SB Gao, YJ Li. Efficient Illuminant Estimation for Color Constancy Using Grey Pixels. CVPR, 2015. [Codes]
  • XS Zhang, KF Yang, YJ Li. Haze Removal with Channel-wise Scattering Coefficient Awareness based on Grey Pixels. Optics Express, 2021
  • C Cheng, KF Yang*, XM Wan, LLH Chen, YJ Li. Nighttime Color Constancy Using Robust Gray Pixels. JOSA A, 2024. [Codes]
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    Computer Vision in Traffic Scenes

  • FY Luo, YJ Cao, KF Yang*, et al. Memory-Guided Collaborative Attention for Nighttime Thermal Infrared Image Colorization of Traffic Scenes. IEEE TITS, 2024.
  • H Zhang, KF Yang, YJ Li, LLH Chan. Self-supervised network for low-light traffic image enhancement based on deep noise and artifacts removal.CVIU, 2024.
  • H Zhang, KF Yang, YJ Li, LLH Chan. Night-Time Vehicle Detection Based on Hierarchical Contextual Information. IEEE TITS, 2024.
  • FY Luo, SL Liu, YJ Cao, KF Yang, et al. Nighttime Thermal Infrared Image Colorization with Feedback-based Object Appearance Learning. IEEE TCSVT, 2024.
  • H Kuang, KF Yang, L Chen, YJ Li, LLH Chan, H Yan. Bayes Saliency Based Object Proposal Generator for Nighttime Traffic Images. IEEE TITS, 2018.
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    Bio-inspired Image Enhancement

  • KF Yang, C Cheng, SX Zhao, HM Yan, XS Zhang, YJ Li. Learning to Adapt to Light. IJCV, 2023. [Codes]
  • XS Zhang, YB Yu, KF Yang, YJ Li. A Fish Retina-inspired Single Image Dehazing Method. IEEE TCSVT, 2022.
  • KF Yang, XS Zhang, YJ Li. A Biological Vision Inspired Framework for Image Enhancement in Poor Visibility Conditions. IEEE TIP, 2020. [Codes]
  • XS Zhang, KF Yang, J Zhou, YJ Li. Retina Inspired Tone Mapping Method for High Dynamic Range Images. Optics Express, 2020.
  • KF Yang, H Li, HL Kuang, CY Li, YJ Li. An Adaptive Method for Image Dynamic Range Adjustment. IEEE TCSVT, 2019. [Codes]
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    Guided Attention and Saliency Detection

  • P Peng, KF Yang*, SQ Liang, YJ Li. Contour-guided Saliency Detection with Long-range Interactions. Neurocomputing, 2022. [Codes]
  • DH He, KF Yang*, XM Wan, F Xiao, HM Yan, YJ Li. A New Representation of Scene Layout Improves Saliency Detection in Traffic Scenes. Expert Syst. Appl.,2022.
  • P Peng, KF Yang, FY Luo, YJ Li. Saliency Detection Inspired by Topological Perception Theory. IJCV, 2021. [Codes]
  • KF Yang, H Li, CY Li, YJ Li. A Unified Framework for Salient Structure Detection by Contour-Guided Visual Search. IEEE TIP, 2016. [Codes]
  • T Deng, KF Yang, YJ Li, HM Yan. Where Does the Driver Look? Top-Down-Based Saliency Detection in a Traffic Driving Environment. IEEE TITS, 2016.
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    Computational Models of Visual Receptive Field

  • KF Yang, SB Gao, CF Guo, CY Li, YJ Li. Boundary Detection Using Double-Opponency and Spatial Sparseness Constraint. IEEE TIP, 2015. [Codes]
  • KF Yang, CY Li, YJ Li. Multifeature-based Surround Inhibition Improves Contour Detection in Natural Images. IEEE TIP, 2014. [Codes]
  • KF Yang, SB Gao, CY Li, YJ Li. Efficient Color Boundary Detection with Color-opponent Mechanisms. CVPR, 2013. [Codes]
  • SB Gao, KF Yang, CY Li, YJ Li. Color Constancy Using Double-Opponency. IEEE TPAMI, 2015.
  • SB Gao, KF Yang, CY Li, YJ Li. A Color Constancy Model with Double-Opponency Mechanisms. ICCV, 2013.
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    (2) Artificial Intelligence in Medicine

     

    Ophthalmic Image Analysis

  • Y Tan, WD Shen,..., KF Yang*, YJ Li*. Retinal Layer Segmentation in OCT images with Boundary Regression and Feature Polarization. IEEE TMI, 2023.
  • Y Tan, SX Zhao, KF Yang*, YJ Li*. A Lightweight Network Guided with Differential Matched Filtering for Retinal Vessel Segmentation. Comput. Biol. Med., 2023.
  • X Wei, KF Yang, D Bzdok, YJ Li. Orientation and Context Entangled Network for Retinal Vessel Segmentation. Expert Syst. Appl. 2023.
  • Y Tan, KF Yang*, SX Zhao, YJ Li. Retinal Vessel Segmentation with Skeletal Prior and Contrastive Loss. IEEE TMI, 2022. [Codes]
  • J Wang, YJ Li, KF Yang*. Retinal fundus Image Enhancement with Image Decomposition and Visual Adaptation. Comput. Biol. Med., 2021.
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    Professional Activities

    Associate Editor for IET Image Processing.
    Reviewer for IJCV, IEEE T-IP, IEEE T-ITS, IEEE T-CSVT, etc.