Jiawang Bian

Jiawang Bian

Higher Degree by Research Candidate

School of Computer Science

Faculty of Engineering, Computer and Mathematical Sciences

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  • Journals
    Year Citation
    2020 Zhang, L., Shi, Z., Zhou, J. T., Cheng, M. -M., Liu, Y., Bian, J. -W., . . . Shen, C. (2020). Ordered or Orderless: A Revisit for Video based Person Re-Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.
    DOI
    2019 Bian, J. W., Lin, W. Y., Liu, Y., Zhang, L., Yeung, S. K., Cheng, M. M., & Reid, I. (2019). GMS: Grid-Based Motion Statistics for Fast, Ultra-robust Feature Correspondence. International Journal of Computer Vision, 128(6), 1580-1593.
    DOI Scopus2 WoS2
    2019 Liu, Y., Cheng, M., Hu, X., Bian, J., Zhang, L., Bai, X., & Tang, J. (2019). Richer convolutional features for edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(8), 1939-1946.
    DOI Scopus52 WoS43 Europe PMC1
    2019 Zhang, L., Shi, Z., Cheng, M. -M., Liu, Y., Bian, J. -W., Zhou, J. T., . . . Zeng, Z. (2019). Nonlinear Regression via Deep Negative Correlation Learning.. IEEE transactions on pattern analysis and machine intelligence, 1.
    DOI

  • Conference Papers
    Year Citation
    2020 Bian, J., Wu, Y., Zhao, J., Liu, Y., Zhang, L., Cheng, M., & Reid, I. (2020). An evaluation of feature matchers for fundamental matrix estimation. In 30th British Machine Vision Conference 2019, BMVC 2019 (pp. 1-14). online: BMVA.
    Scopus5
    2020 Zhan, H., Weerasekera, C., Bian, J., & Reid, I. (2020). Visual Odometry Revisited: What Should Be Learnt?. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 4203-4210). online: IEEE.
    DOI
    2019 Bian, J. -W., Li, Z., Wang, N., Zhan, H., Shen, C., Cheng, M. -M., & Reid, I. (2019). Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alche-Buc, E. Fox, & R. Garnett (Eds.), ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019) Vol. 32 (pp. 1-12). online: NIPS Proceedings.
    Scopus13 WoS1
    2018 Liu, Y., Jiang, P. T., Petrosyan, V., Li, S. J., Bian, J., Zhang, L., & Cheng, M. M. (2018). DEL: Deep embedding learning for efficient image segmentation. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2018-July (pp. 864-870). International Joint Conferences on Artificial Intelligence Organization.
    DOI Scopus13
    2017 Bian, J., Lin, W. Y., Matsushita, Y., Yeung, S. K., Nguyen, T. D., & Cheng, M. M. (2017). GMS: Grid-based motion statistics for fast, ultra-robust feature correspondence. In Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 Vol. 2017-January (pp. 2828-2837). Honolulu, HI: IEEE.
    DOI Scopus140 WoS90
    2016 Cheng, M. M., Liu, Y., Hou, Q., Bian, J., Torr, P., Hu, S. M., & Tu, Z. (2016). HFS: Hierarchical feature selection for efficient image segmentation. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9907 LNCS (pp. 867-882). Amsterdam, NETHERLANDS: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus32 WoS29
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