Yifan Liu

Lecturer

School of Computer Science

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD - email supervisor to discuss availability.


https://scholar.google.com/citations?user=ksQ4JnQAAAAJ&hl=zh-CN

 

Research Topics:

  • Knowledge Distillation
  • Generative Adversarial Networks
  • Perception Tasks with 2d/3d applications:
    • Semantic Segmentation
    • Object detection
    • Instance segmentation
  • Semi/weakly Supervised Training
  • Network Design:
    • Efficient Models
    • Transformer
    • Dynamic Networks

 

  • Journals

    Year Citation
    2022 Yin, W., Zhang, J., Wang, O., Niklaus, S., Chen, S., Liu, Y., & Shen, C. (2022). Towards Accurate Reconstruction of 3D Scene Shape from A Single Monocular Image. IEEE Transactions on Pattern Analysis and Machine Intelligence, PP, 1-21.
    DOI
    2022 Zhang, J., Liu, Y., Li, Q., He, C., Wang, B., & Wang, T. (2022). Object Relocation Visual Tracking Based on Histogram Filter and Siamese Network in Intelligent Transportation. Sensors, 22(22), 8591.
    DOI
    2021 Yin, W., Liu, Y., & Shen, C. (2021). Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10), 13 pages.
    DOI Scopus2 WoS2
    2020 Zhao, Y., Liu, Y., Shen, C., Gao, Y., & Xiong, S. (2020). MobileFAN: transferring deep hidden representation for face alignment. Pattern Recognition, 100, 10 pages.
    DOI Scopus20 WoS16
    2018 Liu, Y., Qin, Z., Wan, T., & Luo, Z. (2018). Auto-painter: Cartoon image generation from sketch by using conditional Wasserstein generative adversarial networks. NEUROCOMPUTING, 311, 78-87.
    DOI Scopus73 WoS56
  • Book Chapters

    Year Citation
    2022 Ren, X., & Liu, Y. (2022). Semantic-Guided Multi-mask Image Harmonization. In Lecture Notes in Computer Science (Vol. 13697 LNCS, pp. 564-579). Springer Nature Switzerland.
    DOI
  • Conference Papers

    Year Citation
    2022 Sheng, Y., Liu, Y., Zhang, J., Yin, W., Oztireli, A. C., Zhang, H., . . . Benes, B. (2022). Controllable Shadow Generation Using Pixel Height Maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13683 LNCS (pp. 240-256). Springer Nature Switzerland.
    DOI
    2021 Shu, C., Liu, Y., Gao, J., Yan, Z., & Shen, C. (2021). Channel-wise Knowledge Distillation for Dense Prediction. In Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 5291-5300). online: IEEE.
    DOI Scopus8 WoS3
    2021 Li, Z., Liu, Y., Liu, J., Yuan, Y., Raza, A., Huo, H., & Fang, T. (2021). Object relationship graph reasoning for object detection of remote sensing images. In 2021 6th International Conference on Image, Vision and Computing, ICIVC 2021 (pp. 43-48). online: IEEE.
    DOI
    2021 Qian, X., Liu, Y., & Yang, Y. (2021). An accurate threshold insensitive kernel detector for arbitrary shaped text. In Proceedings - International Conference on Pattern Recognition (pp. 3011-3018). online: IEEE.
    DOI
    2021 Liu, Y., Chen, H., Chen, Y., Yin, W., & Shen, C. (2021). Generic Perceptual Loss for Modeling Structured Output Dependencies. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 5420-5428). online: IEEE.
    DOI Scopus6
    2021 Yuan, J., Liu, Y., Shen, C., Wang, Z., & Li, H. (2021). A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation. In Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 8209-8218). online: IEEE.
    DOI Scopus5
    2021 Zhang, B., Liu, Y., Tian, Z., & Shen, C. (2021). Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation. In Advances in Neural Information Processing Systems Vol. 34 (pp. 17388-17399). San Diego, CA, USA: Neural Information Processing Systems Foundation.
    Scopus1
    2021 Cao, Y., Li, Y., Zhang, H., Ren, C., & Liu, Y. (2021). Learning Structure Affinity for Video Depth Estimation. In MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia (pp. 190-198). New York, NY, United States: ACM.
    DOI
    2021 Ren, X., Liu, Y., & Song, C. (2021). A Generative Adversarial Framework For Optimizing Image Matting And Harmonization Simultaneously. In Proceedings - 2021 IEEE International Conference on Image Processing (ICIP) Vol. 2021-September (pp. 1354-1358). online: IEEE.
    DOI Scopus1 WoS1
    2020 Liu, Y., Shen, C., Yu, C., & Wang, J. (2020). Efficient Semantic Video Segmentation with Per-Frame Inference. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12355 LNCS (pp. 352-368). Switzerland: Springer International Publishing.
    DOI Scopus19
    2020 He, T., Liu, Y., Shen, C., Wang, X., & Sun, C. (2020). Instance-Aware Embedding for Point Cloud Instance Segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12375 LNCS (pp. 255-270). Switzerland: Springer Nature.
    DOI Scopus5
    2020 Yu, C., Liu, Y., Gao, C., Shen, C., & Sang, N. (2020). Representative Graph Neural Network. In Proceedings of the 16th European Conference on Computer Vision (ECCV) Vol. VII (pp. 379-396). Switzerland: Springer Nature.
    DOI Scopus20
    2020 Qian, X., Liu, Y., & Yang, Y. (2020). MGPAN: Mask Guided Pixel Aggregation Network. In Proceedings - International Conference on Image Processing, ICIP Vol. 2020-October (pp. 1981-1985). online: IEEE.
    DOI Scopus1
    2019 Yin, W., Liu, Y., Shen, C., & Yan, Y. (2019). Enforcing geometric constraints of virtual normal for depth prediction. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2019) Vol. 2019-October (pp. 5683-5692). Piscataway, NJ: IEEE.
    DOI Scopus164 WoS127
    2019 Liu, S., Zhang, J., Chen, Y., Liu, Y., Qin, Z., & Wan, T. (2019). PIXEL LEVEL DATA AUGMENTATION FOR SEMANTIC IMAGE SEGMENTATION USING GENERATIVE ADVERSARIAL NETWORKS. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Vol. 2019-May (pp. 1902-1906). Brighton, ENGLAND: IEEE.
    DOI Scopus24 WoS20
    2019 Liu, Y., Chen, K., Liu, C., Qin, Z., Luo, Z., & Wang, J. (2019). Structured knowledge distillation for semantic segmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 2599-2608). Long Beach, CA, USA: IEEE COMPUTER SOC.
    DOI Scopus197 WoS85
    2018 Zhu, X., Liu, Y., Li, J., Wan, T., & Qin, Z. (2018). Emotion classification with data augmentation using generative adversarial networks. In D. Phung, V. S. Tseng, G. I. Webb, B. Ho, M. Ganji, & L. Rashidi (Eds.), Advances in Knowledge Discovery and Data Mining Vol. 10939 LNAI (pp. 349-360). New York, USA: Springer International Publishing.
    DOI Scopus85
    2018 Li, L., Liu, Y., Qin, Z., Li, P., & Wan, T. (2018). Logical Parsing from Natural Language Based on a Neural Translation Model. In K. Hasida, & W. Pa Pa (Eds.), Computer Linguistics, 15th International Conference of the Pacific Association for Computational Linguistics, PACLING 2017 Vol. 781 (pp. 115-126). Switzerland: Springer Singapore.
    DOI
    2017 Liu, Y., Qin, Z., Li, P., & Wan, T. (2017). Stock volatility prediction using recurrent neural networks with sentiment analysis. In Advances in Artificial Intelligence Vol. 10350 LNCS (pp. 192-201). Switzerland: Springer.
    DOI Scopus15
  • Current:
    1. Computer Vision (Course Coordinator)
  • During Ph.D.:
    1. Computer Vision (Tutor)
    2. Introduction to Statistic Machine Learning (Tutor)
    3. Mining Big Data (Tutor)
  • In University of Cambridge:
    1. Machine Visual Perception (Lecturer)
  • Current Higher Degree by Research Supervision (University of Adelaide)

    Date Role Research Topic Program Degree Type Student Load Student Name
    2022 Principal Supervisor Efficient deep-learning based dynamic neural representational decoders for high-resolution semanticsegmentation Doctor of Philosophy Doctorate Full Time Mr Bowen Zhang
    2022 Co-Supervisor Weakly Supervised Semantic Segmentation Doctor of Philosophy Doctorate Full Time Mr Choubo Ding
    2022 Co-Supervisor Text Visual Question Answering Doctor of Philosophy Doctorate Full Time Mr Xinyu Wang
    2022 Co-Supervisor Deep Learning, 3D Shape Analysis, Few-shot Learning, Low-supervised Learning, Natural Language Processing Doctor of Philosophy Doctorate Full Time Miss Ziqin Zhou
    2022 Co-Supervisor Computer Vision Doctor of Philosophy Doctorate Full Time Mr Yongtao Ge
    2022 Principal Supervisor Efficient Deep Learning on the Edge Doctor of Philosophy Doctorate Full Time Mr Xu Zhan
    2022 Principal Supervisor Depth Estimation Using Deep Learning Master of Philosophy Master Full Time Mr Jiatong Xia
    2021 Principal Supervisor Towards Accurate Semi-Supervised Semantic Segmentation with Fewer Annotations Doctor of Philosophy Doctorate Full Time Miss Jinchao Ge
  • Past Higher Degree by Research Supervision (University of Adelaide)

    Date Role Research Topic Program Degree Type Student Load Student Name
    2022 - 2022 Co-Supervisor Deep Learning for Robotic Scene Understanding Doctor of Philosophy Doctorate Full Time Mr Libo Sun
  • Position: Lecturer
  • Phone: 83136745
  • Email: yifan.liu04@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 1
  • Org Unit: School of Computer Science

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