Minh Hoai Nguyen

Professor Minh Hoai Nguyen

Professor, Professor

Australian Institute for Machine Learning

Division of Research and Innovation

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

Minh Hoai Nguyen is a Professor of Computer Vision at the Australian Institute for Machine Learning (AIML) and the School of Computer and Mathematical Sciences (CMS) at the University of Adelaide. Before joining the University of Adelaide, he was a tenured Associate Professor at Stony Brook University from 2014 until 2024. During this time, he also took a leave to work at VinAI in Vietnam. He received a Bachelor of Software Engineering from the University of New South Wales in 2006 and a Ph.D. in Robotics from Carnegie Mellon University in 2012. His research interests lie in computer vision and machine learning. In 2012, Nguyen and his coauthor received the Best Student Paper Award at the IEEE Conference On Computer Vision and Pattern Recognition (CVPR).

Google Scholar page: https://scholar.google.com/citations?user=hRV0tY4AAAAJ&hl=en
Personal website: https://minhhoai.net

  • Appointments
    Date Position Institution name
    2024 - ongoing Professor Univesity of Adelaide
    2020 - 2023 Associate Professor Stony Brook University
    2019 - ongoing Consulting Research Scientist VinAI Research
    2014 - 2020 Assistant Professor Stony Brook University
    2013 - 2014 Junior Research Fellow University of Oxford

  • Language Competencies
    Language Competency
    English Can read, write, speak, understand spoken and peer review
    Vietnamese Can read, write, speak, understand spoken and peer review

  • Education
    Date Institution name Country Title
    2006 - 2012 Carnegie Mellon University United States PhD in Robotics
    2002 - 2005 The University of New South Wales Australia Bachelor of Software Engineering

  • Postgraduate Training
    Date Title Institution Country
    2012 - 2014 Postdoctoral Research University of Oxford United Kingdom

  • Research Interests
    Computer Vision Machine learning Artificial Intelligence Video processing Image Processing

  • Journals
    Year Citation
    2023 Bui, H., Nguyen, M. H., Nguyen, D. Q., Pham, L., & Phung, D. (2023). Building and Nurturing AI Development in Vietnam. Communications of the ACM, 66(7), 75-76.
    DOI
    2022 Sun, S., Annadi, R. R., Chaudhri, I., Munir, K., Hajagos, J., Saltz, J., . . . Koraishy, F. M. (2022). Short- and Long-Term Recovery after Moderate/Severe AKI in Patients with and without COVID-19. Kidney360, 3(2), 242-257.
    DOI Scopus9 WoS5 Europe PMC4
    2022 Ali, F. Z., Wengler, K., He, X., Nguyen, M. H., Parsey, R. V., & DeLorenzo, C. (2022). Gradient boosting decision-tree-based algorithm with neuroimaging for personalized treatment in depression. Neuroscience Informatics, 2(4), 100110.
    DOI Scopus9 Europe PMC4
    2021 Zelinsky, G. J., Chen, Y., Ahn, S., Adeli, H., Yang, Z., Huang, L., . . . Hoai, M. (2021). Predicting Goal-directed Attention Control Using Inverse-Reinforcement Learning.. Neurons, behavior, data analysis, and theory, 2021(2).
    DOI Europe PMC5
    2021 Chen, Y., Yang, Z., Ahn, S., Samaras, D., Hoai, M., & Zelinsky, G. (2021). COCO-Search18 fixation dataset for predicting goal-directed attention control. Scientific Reports, 11(1), 11 pages.
    DOI Scopus18 WoS5 Europe PMC6
    2021 Hou, L., Vicente, T. F. Y., Hoai, M., & Samaras, D. (2021). Large Scale Shadow Annotation and Detection Using Lazy Annotation and Stacked CNNs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(4), 1337-1351.
    DOI Scopus19 WoS8
    2021 Wei, Z., Wang, B., Hoai, M., Zhang, J., Shen, X., Lin, Z., . . . Samaras, D. (2021). Sequence-to-Segments Networks for Detecting Segments in Videos. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(3), 1009-1021.
    DOI Scopus9 WoS12 Europe PMC1
    2021 Do, N., Truong, D., Nguyen, D., Hoai, M., & Pham, C. (2021). Self-controlling photonic-on-chip networks with deep reinforcement learning. Scientific Reports, 11(1), 18 pages.
    DOI Scopus3 WoS1
    2021 Huang, X., Jamonnak, S., Zhao, Y., Wang, B., Hoai, M., Yager, K., & Xu, W. (2021). Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images. IEEE Transactions on Visualization and Computer Graphics, 27(2), 1312-1321.
    DOI Scopus7 WoS4 Europe PMC1
    2020 Chaudhri, I., Moffitt, R., Taub, E., Annadi, R. R., Hoai, M., Bolotova, O., . . . Koraishy, F. M. (2020). Association of Proteinuria and Hematuria with Acute Kidney Injury and Mortality in Hospitalized Patients with COVID-19. Kidney and Blood Pressure Research, 45(6), 1018-1032.
    DOI Scopus46 WoS35 Europe PMC33
    2018 Liu, Y., Hoai, M., Shao, M., & Kim, T. K. (2018). Latent Bi-Constraint SVM for Video-Based Object Recognition. IEEE Transactions on Circuits and Systems for Video Technology, 28(10), 3044-3052.
    DOI Scopus6 WoS5
    2018 Wang, B., & Hoai, M. (2018). Back to the beginning: Starting point detection for early recognition of ongoing human actions. Computer Vision and Image Understanding, 175, 24-31.
    DOI Scopus8 WoS5
    2018 Vicente, T. F. Y., Hoai, M., & Samaras, D. (2018). Leave-One-Out Kernel Optimization for Shadow Detection and Removal. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(3), 682-695.
    DOI Scopus128 WoS83 Europe PMC7
    2017 Wei, Z., Adeli, H., Hoai, M., Zelinsky, G., & Samaras, D. (2017). Predicting Scanpath Agreement during Scene Viewing using Deep Neural Networks. Journal of Vision, 17(10), 749.
    DOI
    2014 Hoai, M., & De La Torre, F. (2014). Max-margin early event detectors. International Journal of Computer Vision, 107(2), 191-202.
    DOI Scopus174 WoS141
    2014 Hoai, M., Torresani, L., De La Torre, F., & Rother, C. (2014). Learning discriminative localization from weakly labeled data. Pattern Recognition, 47(3), 1523-1534.
    DOI Scopus31 WoS30
    2010 Nguyen, M. H., & De La Torre, F. (2010). Metric learning for image alignment. International Journal of Computer Vision, 88(1), 69-84.
    DOI Scopus15 WoS11
    2010 Nguyen, M. H., & de la Torre, F. (2010). Optimal feature selection for support vector machines. Pattern Recognition, 43(3), 584-591.
    DOI Scopus196 WoS148
    1988 DERYCKE, A., VIEVILLE, C., POISSON, D., STACH, C., & NGUYEN, M. H. (1988). NANORESEAU, EDUCATIONAL UTILIZATION OF A LOCAL-NETWORK. TSI-TECHNIQUE ET SCIENCE INFORMATIQUES, 7(1), 7-20.
    - Zelinsky, G. J., Ahn, S., Yang, Z., Chen, Y., Mondal, S., Hoai, M., & Samaras, D. (n.d.). Reward Maps Predict Target-present and Target-absent Visual Search. Journal of Vision, 23(9), 5161.
    DOI

  • Conference Papers
    Year Citation
    2025 Mondal, S., Ahn, S., Yang, Z., Balasubramanian, N., Samaras, D., Zelinsky, G., & Hoai, M. (2025). Look Hear: Gaze Prediction for Speech-Directed Human Attention. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 15100 LNCS (pp. 236-255). Springer Nature Switzerland.
    DOI
    2024 Chandran, P., Huang, Y., Munsell, J., Howatt, B., Wallace, B., Wilson, L., . . . Loschky, L. C. (2024). Characterizing Learners' Complex Attentional States During Online Multimedia Learning Using Eye-tracking, Egocentric Camera, Webcam, and Retrospective recalls. In Proceedings of the 2024 Symposium on Eye Tracking Research and Applications (pp. 7 pages). Online: ACM.
    DOI Scopus2
    2024 Rebello, N. S., Munsell, J., Chandran, P., Loschky, L. C., Huang, Y., Hoai, M., & D�Mello, S. (2024). Mapping students� self-reported cognitive load, situational engagement, and attentional-cognitive states in an online multimedia learning module. In 2024 Physics Education Research Conference Proceedings (pp. 354-360). Boston Massachusetts: American Association of Physics Teachers.
    DOI
    2024 Nguyen, P., Do, A., & Hoai, M. (2024). Detecting Omissions in Geographic Maps through Computer Vision. In 2024 International Conference on Multimedia Analysis and Pattern Recognition, MAPR 2024 - Proceedings Vol. 6 (pp. 1-6). Da Nang: IEEE.
    DOI
    2024 Yang, Z., Mondal, S., Ahn, S., Xue, R., Zelinsky, G., Hoai, M., & Samaras, D. (2024). Unifying Top-Down and Bottom-Up Scanpath Prediction Using Transformers. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 1683-1693). Seattle, WA, USA: IEEE.
    DOI
    2024 Pham, B. -D., Tran, P., Tran, A., Pham, C., Nguyen, R., & Hoai, M. (2024). Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Vol. 30 (pp. 2804-2813). Seattle, WA, USA: IEEE.
    DOI
    2024 Lee, S., Lu, Z., Zhang, Z., Hoai, M., & Elhamifar, E. (2024). Error Detection in Egocentric Procedural Task Videos. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Vol. abs/2105.10859 (pp. 18655-18666). Seattle, WA, USA: IEEE.
    DOI
    2024 Narasimhaswamy, S., Bhattacharya, U., Chen, X., Dasgupta, I., Mitra, S., & Hoai, M. (2024). HanDiffuser: Text-to-Image Generation with Realistic Hand Appearances. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Vol. 23 (pp. 2468-2479). Seattle, WA, USA: IEEE.
    DOI
    2024 Narasimhaswamy, S., Nguyen, H. A., Huang, L., & Hoai, M. (2024). HOIST-Former: Hand-Held Objects Identification, Segmentation, and Tracking in the Wild. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2351-2361). Seattle, WA, USA: IEEE.
    DOI
    2024 Huang, Y., Nguyen, D. D., Nguyen, L., Pham, C., & Hoai, M. (2024). Count What You Want: Exemplar Identification and Few-Shot Counting of Human Actions in the Wild. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 10057-10065). Online: AAAI.
    DOI
    2023 Ghosh, S., Aggarwal, T., Hoai, M., & Balasubramanian, N. (2023). Text-Derived Knowledge Helps Vision: A Simple Cross-modal Distillation for Video-based Action Anticipation. In I. Augenstein, & A. Vlachos (Eds.), Proceedings OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EACL 2023 (pp. 1882-1897). Online: ASSOC COMPUTATIONAL LINGUISTICS-ACL.
    2023 Ghosh, S., Aggarwal, T., Hoai, M., & Balasubramanian, N. (2023). Text-Derived Knowledge Helps Vision: A Simple Cross-modal Distillation for Video-based Action Anticipation. In EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2023 (pp. 1837-1852). Dubrovnik, Croatia: ACL Anthology.
    Scopus3
    2023 Huang, Y., Ranjan, V., & Hoai, M. (2023). Interactive Class-Agnostic Object Counting. In Proceedings of the IEEE International Conference on Computer Vision (pp. 22255-22265). Paris, France: IEEE.
    DOI Scopus2
    2023 Zhang, Z., & Hoai, M. (2023). Object Detection with Self-Supervised Scene Adaptation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2023-June (pp. 21589-21599). Vancouver, CANADA.: IEEE COMPUTER SOC.
    DOI Scopus5
    2023 Pham, B. D., Tran, P., Tran, A., Pham, C., Nguyen, R., & Hoai, M. (2023). HyperCUT: Video Sequence from a Single Blurry Image using Unsupervised Ordering. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2023-June (pp. 9843-9852). Online: IEEE COMPUTER SOC.
    DOI Scopus1
    2023 Mondal, S., Yang, Z., Ahn, S., Samaras, D., Zelinsky, G., & Hoai, M. (2023). Gazeformer: Scalable, Effective and Fast Prediction of Goal-Directed Human Attention. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2023-June (pp. 1441-1450). Vancouver, BC, CANADA: IEEE COMPUTER SOC.
    DOI Scopus9 WoS1
    2023 Miao, Q., Hoai, M., & Samaras, D. (2023). Patch-level Gaze Distribution Prediction for Gaze Following. In Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023 (pp. 880-889). Waikoloa, HI, USA: IEEE COMPUTER SOC.
    DOI Scopus6
    2023 Tran, V., Balasubramanian, N., & Hoai, M. (2023). From Within to Between: Knowledge Distillation for Cross Modality Retrieval. In L. Wang, J. Gall, T. J. Chin, I. Sato, & R. Chellappa (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13844 LNCS (pp. 605-622). Macao, PEOPLES R CHINA: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI
    2023 Tran, B., Hua, B. S., Tran, A. T., & Hoai, M. (2023). Self-supervised Learning with Multi-view Rendering for 3D Point Cloud Analysis. In J. Gall, T. J. Chin, I. Sato, R. Chellappa, & L. Wang (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13841 LNCS (pp. 413-431). Macao, China: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus1
    2023 Ranjan, V., & Nguyen, M. H. (2023). Exemplar Free Class Agnostic Counting. In L. Wang, J. Gall, T. J. Chin, I. Sato, & R. Chellappa (Eds.), Computer Vision – ACCV 2022 16th Asian Conference on Computer Vision, Proceedings Vol. 13844 (pp. 71-87). Macao, China: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus1 WoS1
    2022 Ho, L. N., Tran, A. T., Phung, Q., & Hoai, M. (2022). Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images. In Proceedings of the IEEE International Conference on Computer Vision (pp. 12580-12590). Montreal, QC, Canada: IEEE.
    DOI Scopus7 WoS1
    2022 Nguyen, T., Pham, C., Nguyen, K., & Hoai, M. (2022). Few-Shot Object Counting and Detection. In S. Avidan, G. Brostow, M. Cisse, G. M. Farinella, & T. Hassner (Eds.), European Conference on Computer Vision. Computer Vision - ECCV Vol. 13680 (pp. 348-365). Tel Aviv, ISRAEL: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus13 WoS2
    2022 Yang, Z., Mondal, S., Ahn, S., Zelinsky, G., Hoai, M., & Samaras, D. (2022). Target-Absent Human Attention. In S. Avidan, G. Brostow, M. Cisse, G. M. Farinella, & T. Hassner (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13664 (pp. 52-68). ISRAEL, Tel Aviv: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus5 WoS1
    2022 Ranjan, V., & Hoai, M. (2022). Vicinal Counting Networks. In Conference on Computer Vision and Pattern Recognition Workshops IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Vol. 2022-June (pp. 4220-4229). New Orleans, LA, USA: IEEE.
    DOI Scopus9 WoS1
    2022 Chen, Y., Yang, Z., Chakraborty, S., Mondal, S., Ahn, S., Samaras, D., . . . Zelinsky, G. (2022). Characterizing Target-absent Human Attention. In Conference on Computer Vision and Pattern Recognition Workshops IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Vol. 2022 (pp. 5027-5036). New Orleans, LA, USA: IEEE.
    DOI Scopus5
    2022 Huang, M., Narasimhaswamy, S., Vazir, S., Ling, H., & Hoai, M. (2022). Forward Propagation, Backward Regression, and Pose Association for Hand Tracking in the Wild. In Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 6396-6406). New Orleans. LA, USA: IEEE.
    DOI Scopus7
    2022 Narasimhaswamy, S., Nguyen, T., Huang, M., & Hoai, M. (2022). Whose Hands are These? Hand Detection and Hand-Body Association in the Wild. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 4879-4889). New Orleans, LA, USA: IEEE COMPUTER SOC.
    DOI Scopus13 WoS3
    2021 Nguyen, T., Tran, A. T., & Hoai, M. (2021). Lipstick ain't enough: Beyond color matching for in-the-wild makeup transfer. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 13300-13309). Nashville, TN, USA: IEEE COMPUTER SOC.
    DOI Scopus33 WoS20
    2021 Tran, V., Balasubramanian, N., & Hoai, M. (2021). PROGRESSIVE KNOWLEDGE DISTILLATION FOR EARLY ACTION RECOGNITION. In Proceedings - International Conference on Image Processing, ICIP Vol. 2021-September (pp. 2583-2587). Anchorage, AK, USA: IEEE.
    DOI Scopus7 WoS6
    2021 Ranjan, V., Sharma, U., Nguyen, T., & Hoai, M. (2021). Learning To Count Everything. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 3393-3402). Nashville, TN, USA: IEEE COMPUTER SOC.
    DOI Scopus73 WoS19
    2021 Nguyen, N., Nguyen, T., Tran, V., Tran, M. T., Ngo, T. D., Nguyen, T. H., & Hoai, M. (2021). Dictionary-guided Scene Text Recognition. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 7379-7388). ELECTR NETWORK: IEEE COMPUTER SOC.
    DOI Scopus45 WoS18
    2021 Park, S., Hoai, M., Bhattacharya, A., & Das, S. R. (2021). Adaptive streaming of 360-degree videos with reinforcement learning. In Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021 (pp. 1838-1847). Waikoloa, HI, USA: IEEE COMPUTER SOC.
    DOI Scopus18 WoS9
    2021 Wang, Y., Bertasius, G., Oh, T. H., Gupta, A., Hoai, M., & Torresani, L. (2021). Supervoxel attention graphs for long-range video modeling. In Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021 (pp. 155-166). Waikoloa, HI, USA: IEEE COMPUTER SOC.
    DOI Scopus4 WoS1
    2021 Abousamra, S., Hoai, M., Samaras, D., & Chen, C. (2021). Localization in the Crowd with Topological Constraints. In 35th AAAI Conference on Artificial Intelligence, AAAI 2021 Vol. 2A (pp. 872-881). Virtual, Online: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
    Scopus83 WoS33
    2021 Tran, V., Wang, Y., Zhang, Z., & Hoai, M. (2021). KNOWLEDGE DISTILLATION FOR HUMAN ACTION ANTICIPATION. In Proceedings - International Conference on Image Processing, ICIP Vol. 2021-September (pp. 2518-2522). Anchorage, AK, USA: IEEE.
    DOI Scopus4
    2021 Tran, P., Tran, A. T., Phung, Q., & Hoai, M. (2021). Explore image deblurring via encoded blur kernel space. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 11951-11960). Nashville, TN, USA: IEEE COMPUTER SOC.
    DOI Scopus50 WoS25
    2021 Huynh, C., Tran, A. T., Luu, K., & Hoai, M. (2021). Progressive semantic segmentation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 16750-16759). Nashville, TN, USA: IEEE COMPUTER SOC.
    DOI Scopus75 WoS31
    2021 Zhang, Z., Koraishy, F. M., & Hoai, M. (2021). Exemplar-Based Early Event Prediction in Video. In 32nd British Machine Vision Conference, BMVC 2021. Virtual, Online: British Machine Vision Association, BMVA.
    2020 Wang, Y., Tran, V., Bertasius, G., Torresani, L., & Hoai, M. (2020). Attentive Action and Context Factorization. In 31st British Machine Vision Conference, BMVC 2020. Virtual, Online: British Machine Vision Association, BMVA.
    Scopus3
    2020 Nguyen, M. T., Phung, D., Hoai, M., & Nguyen, T. H. (2020). Structural and functional decomposition for personality image captioning in a communication game. In Findings of the Association for Computational Linguistics Findings of ACL: EMNLP 2020 (pp. 4587-4593). Virtual, Online: Association for Computational Linguistics (ACL).
    Scopus2
    2020 Wang, B., Liu, H., Samaras, D., & Hoai, M. (2020). Distribution matching for crowd counting. In Advances in Neural Information Processing Systems Vol. 2020-December. Virtual, Online: Neural information processing systems foundation.
    Scopus207
    2020 Narasimhaswamy, S., Nguyen, T., & Hoai, M. (2020). Detecting hands and recognizing physical contact in the wild. In Advances in Neural Information Processing Systems Vol. 2020-December. Virtual, Online: Neural information processing systems foundation.
    Scopus27
    2020 Ranjan, V., Wang, B., Shah, M., & Hoai, M. (2020). Uncertainty Estimation and Sample Selection for Crowd Counting. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12626 LNCS (pp. 375-391). Virtual, Online: Springer International Publishing.
    DOI Scopus4
    2020 Wei, Z., Zhang, J., Lin, Z., Lee, J. Y., Balasubramanian, N., Hoai, M., & Samaras, D. (2020). Learning Visual Emotion Representations from Web Data. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 13103-13112). Seattle, WA, USA: IEEE.
    DOI Scopus36
    2020 Yang, Z., Huang, L., Chen, Y., Wei, Z., Ahn, S., Zelinsky, G., . . . Hoai, M. (2020). Predicting Goal-Directed Human Attention Using Inverse Reinforcement Learning. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2020 (pp. 190-199). Seattle, WA, USA: IEEE.
    DOI Scopus50 WoS32 Europe PMC7
    2020 Shilkrot, R., Narasimhaswamy, S., Vazir, S., & Hoai, M. (2020). WorkingHands: A hand-tool assembly dataset for image segmentation and activity mining. In 30th British Machine Vision Conference 2019, BMVC 2019. Cardiff: BMVA Press.
    Scopus7
    2020 Wang, B., Huang, L., & Hoai, M. (2020). Active vision for early recognition of human actions. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1078-1088). Seattle, WA, USA: IEEE.
    DOI Scopus11 WoS3
    2019 Zelinsky, G., Yang, Z., Huang, L., Chen, Y., Ahn, S., Wei, Z., . . . Hoai, M. (2019). Benchmarking gaze prediction for categorical visual search. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2019-June (pp. 828-836). CA, Long Beach: IEEE.
    DOI Scopus31 WoS14
    2019 Narasimhaswamy, S., Wei, Z., Wang, Y., Zhang, J., & Nguyen, M. H. (2019). Contextual attention for hand detection in the wild. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 9566-9575). SOUTH KOREA, Seoul: IEEE.
    DOI Scopus48 WoS25
    2019 Wang, Y., Huang, H., Wang, C., He, T., Wang, J., & Hoai, M. (2019). GIF2VIDEO: Color dequantization and temporal interpolation of GIF images. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 1419-1428). CA, Long Beach: IEEE COMPUTER SOC.
    DOI Scopus11 WoS7
    2019 Rebello, N. S., Minh, H. N., Wang, Y., Zu, T., Hutson, J., & Loschky, L. C. (2019). Machine learning predicts responses to conceptual tasks using eye movements. In A. Traxler, Y. Cao, & S. Wolf (Eds.), 2018 PHYSICS EDUCATION RESEARCH CONFERENCE (PERC) (pp. 4 pages). DC, Washington: AMER ASSOC PHYSICS TEACHERS.
    WoS1
    2018 Wei, Z., Wang, B., Hoai, M., Zhang, J., Lin, Z., Shen, X., . . . Samaras, D. (2018). Sequence-to-segments networks for segment detection. In S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. CesaBianchi, & R. Garnett (Eds.), Advances in Neural Information Processing Systems Vol. 2018-December (pp. 3507-3516). CANADA, Montreal: NEURAL INFORMATION PROCESSING SYSTEMS (NIPS).
    Scopus10
    2018 Wei, Z., Zhang, J., Shen, X., Lin, Z., Mech, R., Hoai, M., & Samaras, D. (2018). Good View Hunting: Learning Photo Composition from Dense View Pairs. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 5437-5446). UT, Salt Lake City: IEEE.
    DOI Scopus70 WoS43
    2018 Wang, Y., & Hoai, M. (2018). Pulling Actions out of Context: Explicit Separation for Effective Combination. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 7044-7053). UT, Salt Lake City: IEEE.
    DOI Scopus20
    2018 Wang, Y., Tran, V. Q., & Nguyen, M. H. (2018). Eigen-evolution dense trajectory descriptors. In Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018 (pp. 473-479). PEOPLES R CHINA, Xi an: IEEE.
    DOI Scopus4 WoS3
    2018 Ranjan, V., Le, H., & Hoai, M. (2018). Iterative crowd counting. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11211 LNCS (pp. 278-293). GERMANY, Munich: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus72 WoS172
    2018 Wang, Y., Wang, L., You, Y., Zou, X., Chen, V., Li, S., . . . Weinberger, K. Q. (2018). Resource Aware Person Re-identification across Multiple Resolutions. In 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (pp. 8042-8051). UT, Salt Lake City: IEEE.
    DOI WoS210
    2018 Le, H., Vicente, T. F. Y., Nguyen, V., Hoai, M., & Samaras, D. (2018). A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11206 LNCS (pp. 680-696). GERMANY, Munich: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus27 WoS62
    2018 Wang, B., & Hoai, M. (2018). Predicting body movement and recognizing actions: An integrated framework for mutual benefits. In Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018 (pp. 341-348). PEOPLES R CHINA, Xi an: IEEE.
    DOI Scopus11 WoS3
    2017 Nguyen, V., Vicente, T. F. Y., Zhao, M., Hoai, M., & Samaras, D. (2017). Shadow Detection with Conditional Generative Adversarial Networks. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2017-October (pp. 4520-4528). ITALY, Venice: IEEE.
    DOI Scopus179 WoS122
    2017 Wang, B., Yager, K., Yu, D., & Hoai, M. (2017). X-Ray scattering image classification using deep learning. In Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017 (pp. 697-704). CA, Santa Rosa: IEEE.
    DOI Scopus47 WoS29
    2017 Ma, K., Hoai, M., & Samaras, D. (2017). Large-scale continual road inspection: Visual infrastructure assessment in the wild. In British Machine Vision Conference 2017, BMVC 2017. British Machine Vision Association.
    DOI Scopus19
    2016 Wang, Y., & Hoai, M. (2016). Improving Human Action Recognition by Non-action Classification. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 2698-2707). WA, Seattle: IEEE.
    DOI Scopus14 WoS6
    2016 Vicente, T. F. Y., Hoai, M., & Samaras, D. (2016). Noisy Label Recovery for Shadow Detection in Unfamiliar Domains. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 3783-3792). WA, Seattle: IEEE.
    DOI Scopus32 WoS19
    2016 Vicente, T. F. Y., Hou, L., Yu, C. P., Hoai, M., & Samaras, D. (2016). Large-scale training of shadow detectors with noisily-annotated shadow examples. 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. 9910 LNCS (pp. 816-832). NETHERLANDS, Amsterdam: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus170 WoS115
    2016 Wei, Z., & Hoai, M. (2016). Region Ranking SVM for Image Classification. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 2987-2996). WA, Seattle: IEEE.
    DOI Scopus23 WoS12
    2016 Wei, Z., Adeli, H., Zelinsky, G., Hoai, M., & Samaras, D. (2016). Learned region sparsity and diversity also predict visual attention. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, & R. Garnett (Eds.), Advances in Neural Information Processing Systems Vol. 29 (pp. 1902-1910). SPAIN, Barcelona: NEURAL INFORMATION PROCESSING SYSTEMS (NIPS).
    Scopus9 WoS1
    2016 Wang, B., Guan, Z., Yao, S., Qin, H., Nguyen, M. H., Yager, K., & Yu, D. (2016). Deep learning for analysing synchrotron data streams. In 2016 New York Scientific Data Summit, NYSDS 2016 - Proceedings (pp. 5 pages). NY, New York: IEEE.
    DOI Scopus8
    2015 Hoai, M., & Zisserman, A. (2015). Improving human action recognition using score distribution and ranking. In D. Cremers, I. Reid, H. Saito, & M. H. Yang (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9007 (pp. 3-20). SINGAPORE, Singapore: SPRINGER-VERLAG BERLIN.
    DOI Scopus27 WoS19
    2015 Kwon, H., Yun, K., Hoai, M., & Samaras, D. (2015). Recognizing cultural events in images: A study of image categorization models. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2015-October (pp. 51-57). MA, Boston: IEEE.
    DOI Scopus6
    2015 Hoai, M., & Zisserman, A. (2015). Thread-safe: Towards recognizing human actions across shot boundaries. In D. Cremers, I. Reid, H. Saito, & M. H. Yang (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9006 (pp. 222-237). SINGAPORE, Singapore: SPRINGER-VERLAG BERLIN.
    DOI Scopus2 WoS2
    2015 Vicente, T. F. Y., Hoai, M., & Samaras, D. (2015). Leave-one-out kernel optimization for shadow detection. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2015 International Conference on Computer Vision, ICCV 2015 (pp. 3388-3396). CHILE, Santiago: IEEE.
    DOI Scopus46 WoS29
    2014 Hoai, M., & Zisserman, A. (2014). Talking heads: Detecting humans and recognizing their interactions. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 875-882). OH, Columbus: IEEE.
    DOI Scopus45 WoS20
    2014 Hoai, M., Ladický, L., & Zisserman, A. (2014). Action recognition from weak alignment of body parts. In BMVC 2014 - Proceedings of the British Machine Vision Conference 2014 (pp. 86.1-86.12). British Machine Vision Association.
    DOI Scopus13
    2014 Hoai, M. (2014). Regularized Max Pooling for image categorization. In BMVC 2014 - Proceedings of the British Machine Vision Conference 2014 (pp. 32.1-32.12). British Machine Vision Association.
    DOI Scopus52
    2013 Hoai, M., & Zisserman, A. (2013). Discriminative sub-categorization. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1666-1673). OR, Portland: IEEE.
    DOI Scopus43 WoS21
    2012 Hoai, M., & De La Torre, F. (2012). Max-margin early event detectors. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2863-2870). RI, Providence: IEEE.
    DOI Scopus124 WoS56
    2012 Hoai, M., & De La Torre, F. (2012). Maximum margin temporal clustering. In Journal of Machine Learning Research Vol. 22 (pp. 520-528).
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    2011 Hoai, M., Lan, Z. Z., & De La Torre, F. (2011). Joint segmentation and classification of human actions in video. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 3265-3272). CO, Colorado Springs: IEEE.
    DOI Scopus206 WoS24
    2010 Simon, T., Nguyen, M. H., De La Torre, F., & Cohn, J. F. (2010). Action unit detection with segment-based SVMs. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2737-2744). IEEE.
    DOI Scopus66
    2009 Cohn, J. F., Kruez, T. S., Matthews, I., Yang, Y., Nguyen, M. H., Padilla, M. T., . . . De La Torre, F. (2009). Detecting depression from facial actions and vocal prosody. In Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009 (pp. 1-7). IEEE.
    DOI Scopus373
    2009 Nguyen, M. H., & De La Torre, F. (2009). Robust kernel principal component analysis. In Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference (pp. 1185-1192).
    Scopus41
    2009 Nguyen, M. H., Torresani, L., De La Torre, F., & Rother, C. (2009). Weakly supervised discriminative localization and classification: A joint learning process. In Proceedings of the IEEE International Conference on Computer Vision (pp. 1925-1932). JAPAN, Kyoto: IEEE.
    DOI Scopus146 WoS85
    2008 Minh, H. N., & De La Torre, F. (2008). Local minima free parameterized appearance models. In 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR (pp. 1412-1419). AK, Anchorage: IEEE.
    DOI Scopus24
    2008 Nguyen, M. H., & De La Torre, F. (2008). Learning image alignment without local minima for face detection and tracking. In 2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008 (pp. 466-472). NETHERLANDS, Amsterdam: IEEE.
    DOI Scopus8
    2008 Nguyen, M. H., Lalonde, J. F., Efros, A. A., & De La Torre, F. (2008). Image-based shaving. In Computer Graphics Forum Vol. 27 (pp. 627-635). GREECE, Crete: WILEY.
    DOI Scopus38 WoS28
    2008 De La Torre, F., & Minh, H. N. (2008). Parameterized kernel principal component analysis: Theory and applications to supervised and unsupervised image alignment. In 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR (pp. 1404-1411). AK, Anchorage: IEEE.
    DOI Scopus35
    2008 Nguyen, M. H., Perez, J., & Torre, F. D. L. (2008). Facial feature detection with optimal pixel reduction SVM. In 2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008 (pp. 460-465). NETHERLANDS, Amsterdam: IEEE.
    DOI Scopus36
    2006 Nguyen, M. H., & Wobcke, W. (2006). A flexible framework for SharedPlans. In A. Sattar, & B. H. Kang (Eds.), AI 2006: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS Vol. 4304 (pp. 393-+). AUSTRALIA, Hobart: SPRINGER-VERLAG BERLIN.
    WoS2
    2003 Chan, K., Chen, A. N., Liang, Z. C. L., Michail, A., Nguyen, M. H., & Seow, N. (2003). DRT: A tool for design recovery of interactive graphical applications. In 25TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, PROCEEDINGS (pp. 814-815). OR, PORTLAND: IEEE COMPUTER SOC.
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Teaching at Stony Brook University

Spring 2021: CSE512 – Machine Learning – Graduate

Fall 2020: CSE353 – Machine Learning – Undergraduate

Spring 2020: CSE615 – Advanced Computer Vision – Graduate

Fall 2019: CSE512 – Machine Learning – Graduate

Spring 2019: CSE378 – Introduction to Robotics – Undergraduate

Fall 2018: CSE512 – Machine Learning – Graduate

Spring 2018: CSE512 – Machine Learning – Graduate

Spring 2018: CSE378 – Introduction to Robotics – Undergraduate

Fall 2016: CSE527 – Introduction to Computer Vision – Graduate

Spring 2016: CSE512 – Machine Learning – Graduate

Spring 2015: CSE525 – Introduction to Robotics – Graduate

Fall 2014: CSE594 – Video Analysis – Graduate

 

  • Position: Professor, Professor
  • Phone: 83133898
  • Email: minhhoai.nguyen@adelaide.edu.au
  • Campus: Lot 14
  • Building: Australian Institute for Machine Learning Building, floor First Floor
  • Room: 1.05
  • Org Unit: Australian Institute for Machine Learning - Projects, School of Computer and Mathematical Sciences
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