WS03: Parallel Vision in Intelligent Vehicles
( CFP )

Workshop Code: 319nv

Time: 8:30-12:00


  • Kunfeng Wang
    Affiliation: Institute of Automation, Chinese Academy of Sciences, China and Qingdao Academy of Intelligent Industries, China

Scope and Goals

Recent advances in computer vision (including object detection, segmentation, tracking, and scene undertanding) have promoted the development of intelligent vehicles significantly. However, vision-based methods for intelligent vehicles research require large amounts of annotated images for training, testing, and explaining the computer vision models effectively, while the collection of large-scale, diversified labelled data from the real world is both expensive and error-prone. To tackle these issues, we propose parallel vision, which is a virtual-real interactive approach to intelligent visual computing and comprises artificial scenes, computational experiments, and parallel execution. By synthesizing and exploiting virtual images to build more reliable computer vision systems, parallel vision attracts increasly more attention in the community of computer vision and intelligent vehicles.

Topics of Interest

  • Computer graphics and virtual reality for traffic scene simulation
  • Driving simulator to generate photorealistic virtual images
  • Generative models related to virtual traffic images (generative adversarial networks, variational autoencoders, etc.)
  • Neural networks that learn from virtual images
  • Intelligent visual computing with virtual images
  • Virtual and real world adaptation for vehicular vision
  • Evaluation of vehicular vision systems using virtual images
  • Applications of virtual images to intelligent vehicles


  • invited talk1
    Prof. Kunfeng Wang
    Institute of Automation, Chinese Academy of Sciences

  • invited talk2
    Miss. Hui Zhang
    Institute of Automation, Chinese Academy of Sciences

  • invited talk3
    Mr. Wenwen Zhang
    Xi'an Jiaotong University

  • invited talk4
    Mr. Yue Lu
    Institute of Automation, Chinese Academy of Sciences