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Biologically inspired visual computing: the state of the art

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Abstract

Visual information is highly advantageous for the evolutionary success of almost all animals. This information is likewise critical for many computing tasks, and visual computing has achieved tremendous successes in numerous applications over the last 60 years or so. In that time, the development of visual computing has moved forwards with inspiration from biological mechanisms many times. In particular, deep neural networks were inspired by the hierarchical processing mechanisms that exist in the visual cortex of primate brains (including ours), and have achieved huge breakthroughs in many domain-specific visual tasks. In order to better understand biologically inspired visual computing, we will present a survey of the current work, and hope to offer some new avenues for rethinking visual computing and designing novel neural network architectures.

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Acknowledgements

This work was supported in part by the National Key R&D Program of China (2018YFB1004600), the National Natural Science Foundation of China (Grant Nos. 61761146004, 61773375), the Beijing Municipal Natural Science Foundation (Z181100008918010), and Chinese Academy of Sciences (153D31KYSB20160282).

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Authors and Affiliations

  1. Research Center for Research on Intelligent Perception and Computing, Beijing, 100190, China

    Wangli Hao & Zhaoxiang Zhang

  2. National Laboratory of Pattern Recognition, CASIA, Beijing, 100190, China

    Zhaoxiang Zhang

  3. CAS Center for Excellence in Brain Science and Intelligence Technology, CAS, Beijing, 100190, China

    Wei Wang & Zhaoxiang Zhang

  4. University of Chinese Academy of Sciences, Beijing, 100190, China

    Wangli Hao, Wei Wang & Zhaoxiang Zhang

  5. State Key Laboratory of Neuroscience, Shanghai, 200031, China

    Wei Wang

  6. Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China

    Ian Max Andolina & Wei Wang

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  1. Wangli Hao
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Correspondence to Zhaoxiang Zhang.

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Wangli Hao is currently a PhD candidate in the Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences (CAS), China. She received her bachelor’s degree in Shanxi Agricultural University, China in 2011. After that, She received her master’s degree in the Beijing Institute of Technology, China in 2014.

Ian Max Andolina is the Director of the Cognition & Behaviour research platform and Associate Investigator at the Institute of Neuroscience, Chinese Academy of Sciences, China. He obtained a first class degree in Neuroscience at the University of Sussex and a PhD in Visual Neuroscience at University College London (UCL), UK. He worked at UCL specialising on the neurophysiology of the recurrent circuitry between cortical areas and between the visual cortex and thalamus during visual processing of form and motion. He moved to Shanghai to join the Institute of Neuroscience, CAS, China in 2016.

Wei Wang is a Senior Investigator and the Head of the Laboratory of Visual Perceptual Mechanisms at Institute of Neuroscience, CAS, China. He received his MSc and PhD from the University of Science & Technology of China (USTC), China in 1993 and 1998. He was a research fellow and a senior research fellow at University College London (UCL), University of Manchester Institute of Science & Technology (UMIST) and University of Manchester (UM), UK respectively, from 1998 to 2006.

Zhaoxiang Zhang is a professor in the Center for Research on Intelligent Perception and Computing, Institute of Automation, CAS, China. He received his bachelor’s degree in Circuits and Systems from USTC, China in 2004. After that, he was a PhD candidate under the supervision of Professor Tieniu Tan in the National Laboratory of Pattern Recognition, CASIA, where he received his PhD degree in 2009. He joined the School of Computer Science and Engineering, Beihang University, China as an Assistant Professor (2009–2011), an Associate professor (2012–2015) and vice-director of the Department of Computer application technology (2014–2015). In July 2015, he returned to the Institute of Automation, CAS, China.

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Hao, W., Andolina, I.M., Wang, W. et al. Biologically inspired visual computing: the state of the art. Front. Comput. Sci. 15, 151304 (2021). https://doi.org/10.1007/s11704-020-9001-8

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