Jiawang Bian
Higher Degree by Research Candidate
HDR Student
School of Computer Science
Faculty of Sciences, Engineering and Technology
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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.
Scopus1 WoS12021 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.
Scopus32021 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.
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.
Scopus21 WoS122021 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.
Scopus10 WoS8 Europe PMC12021 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.
Scopus10 WoS112021 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.
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.
Scopus9 WoS72019 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.
Scopus165 WoS199 Europe PMC12019 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.
Scopus38 WoS35 -
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.
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.
Scopus32020 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.
Scopus142020 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.
Scopus26 WoS212019 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.
Scopus117 WoS422018 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.
Scopus27 WoS212017 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.
Scopus296 WoS2412016 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.
Scopus48 WoS44
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