Latest News

  • Our paper entitled “The ParallelEye Dataset: A Large Collection of Virtual Images for Traffic Vision Research” is accepted by IEEE Transactions on Intelligent Transportation Systems (IF: 4.051).

  • On June 26, we organized The First Workshop on Parallel Vision in Intelligent Vehicles, in Changshu, Jiangsu, China.

  • Our paper entitled “MFR-CNN: Incorporating Multi-Scale Features and Global Information for Traffic Object Detection” is accepted by IEEE Transactions on Vehicular Technology (IF: 4.066).

  • Kunfeng Wang is elevated to Senior Member of IEEE.

  • Our paper entitled “The ParallelEye-CS Dataset: Constructing Artificial Scenes for Evaluating the Visual Intelligence of Intelligent Vehicles” was accepted by IEEE IV 2018 Workshops.

  • Our paper entitled “Gaze-Aided Eye Detection via Appearance Learning” was accepted by ICPR 2018 (2018 International Conference on Pattern Recognition).

  • Our paper entitled "Generative adversarial networks: introduction and outlook" was rated among the hot papers by IEEE/CAA JAS.

  • Our paper entitled “Background Subtraction Algorithm Based on Bayesian Generative Adversarial Networks” was accepted by Acta Automatica Sinica.

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Latest Publications

  • The ParallelEye Dataset: A Large Collection of Virtual Images for Traffic Vision Research
    Xuan Li, Kunfeng Wang, Yonglin Tian, Lan Yan, Fang Deng, and Fei-Yue Wang, "The ParallelEye Dataset: A Large Collection of Virtual Images for Traffic Vision Research," IEEE Transactions on Intelligent Transportation Systems, August 2018, online available.

    • MFR-CNN: Incorporating Multi-Scale Features and Global Information for Traffic Object Detection
      Hui Zhang, Kunfeng Wang, Yonglin Tian, Chao Gou, and Fei-Yue Wang, "MFR-CNN: Incorporating Multi-Scale Features and Global Information for Traffic Object Detection," IEEE Transactions on Vehicular Technology, June 2018, online available.

      • Generative Adversarial Networks: From Generating Data to Creating Intelligence
        Kunfeng Wang, Wang-Meng Zuo, Ying Tan, Tao Qin, Li Li, and Fei-Yue Wang, "Generative Adversarial Networks: From Generating Data to Creating Intelligence," Acta Automatica Sinica, 2018, vol. 44, no. 5, pp. 769-774.

        • Artificial intelligence test: a case study of intelligent vehicles
          Li Li, Yi-Lun Lin, Nan-Ning Zheng, Fei-Yue Wang, Yuehu Liu, Dongpu Cao, Kunfeng Wang, and Wu-Ling Huang, “Artificial intelligence test: a case study of intelligent vehicles,” Artificial Intelligence Review, April 2018, online available.

          • Background Subtraction Algorithm Based on Bayesian Generative Adversarial Networks
            Wenbo Zheng, Kunfeng Wang, and Fei-Yue Wang, “Background Subtraction Algorithm Based on Bayesian Generative Adversarial Networks,” Acta Automatica Sinica, accepted.

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