Jiawang Bian

Higher Degree by Research Candidate

HDR Student

School of Computer Science

Faculty of Sciences, Engineering and Technology


  • Journals

    Year Citation
    2022 Liu, Y., Cheng, M. M., Fan, D. P., Zhang, L., Bian, J. W., & Tao, D. (2022). Semantic Edge Detection with Diverse Deep Supervision. International Journal of Computer Vision, 130(1), 179-198.
    DOI Scopus8 WoS5
    2021 Wu, Y. H., Liu, Y., Xu, J., Bian, J. W., Gu, Y. C., & Cheng, M. M. (2021). MobileSal: Extremely Efficient RGB-D Salient Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.
    DOI Scopus5
    2021 Bian, J. W., Zhan, H., Wang, N., Chin, T. J., Shen, C., & Reid, I. (2021). Auto-Rectify Network for Unsupervised Indoor Depth Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 pages.
    DOI
    2021 Zhang, L., Shi, Z., Cheng, M. M., Liu, Y., Bian, J. W., Zhou, J. T., . . . Zeng, Z. (2021). Nonlinear Regression via Deep Negative Correlation Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(3), 982-998.
    DOI Scopus30 WoS21
    2021 Zhang, L., Shi, Z., Zhou, J. T., Cheng, M. M., Liu, Y., Bian, J. W., . . . Shen, C. (2021). Ordered or Orderless: A Revisit for Video Based Person Re-Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(4), 1460-1466.
    DOI Scopus12 WoS10 Europe PMC1
    2021 Liu, Y., Zhang, X. Y., Bian, J. W., Zhang, L., & Cheng, M. M. (2021). SAMNet: Stereoscopically Attentive Multi-Scale Network for Lightweight Salient Object Detection. IEEE Transactions on Image Processing, 30, 3804-3814.
    DOI Scopus23 WoS25
    2021 Zhang, L., Shi, Z., Cheng, M. -M., Liu, Y., Bian, J. -W., Zhou, J. T., . . . Zeng, Z. (2021). Correction to “Nonlinear Regression via Deep Negative Correlation Learning”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(6), 2172.
    DOI
    2021 Bian, J., Zhan, H., Wang, N., Li, Z., Zhang, L., Shen, C., . . . Reid, I. (2021). Unsupervised scale-consistent depth learning from video. International Journal of Computer Vision, 129(9), 2548-2564.
    DOI Scopus17 WoS11
    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 Scopus188 WoS276 Europe PMC1
    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 Scopus48 WoS41
  • Conference Papers

    Year Citation
    2022 Bian, J. W., Zhan, H., & Reid, I. (2022). NVSS: High-quality Novel View Selfie Synthesis. In Proceedings - 2021 International Conference on 3D Vision, 3DV 2021 (pp. 1085-1094). online: IEEE.
    DOI
    2021 Zhang, X., Wang, X., Bian, J. W., Shen, C., & You, M. (2021). Diverse Knowledge Distillation for End-to-End Person Search. In 35th AAAI Conference on Artificial Intelligence, AAAI 2021 Vol. 4B (pp. 3412-3420). ELECTR NETWORK: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
    Scopus7 WoS2
    2020 Bian, J. W., Wu, Y. H., Zhao, J., Liu, Y., Zhang, L., Cheng, M. M., & Reid, I. (2020). An evaluation of feature matchers for fundamental matrix estimation. In Proceedings of the 30th British Machine Vision Conference (BMVC 2019) (pp. 1-14). online: BMVA.
    DOI Scopus14
    2020 Zhan, H., Weerasekera, C. S., Bian, J. W., & Reid, I. (2020). Visual odometry revisited: what should be learnt?. In Proceedings of the EEE International Conference on Robotics and Automation, as published in the IEEE Xplore (pp. 4203-4210). online: IEEE.
    DOI Scopus38 WoS27
    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.
    Scopus137 WoS65
    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 J. Lang (Ed.), IJCAI International Joint Conference on Artificial Intelligence Vol. 2018-July (pp. 864-870). Stockholm, SWEDEN: IJCAI-INT JOINT CONF ARTIF INTELL.
    DOI Scopus29 WoS22
    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 Scopus318 WoS265
    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 Scopus48 WoS46
  • Position: HDR Student
  • Email: jiawang.bian@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Org Unit: Australian Institute for Machine Learning - Operations

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