Professor Minh Hoai Nguyen
Professor
Australian Institute for Machine Learning - Operations
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) at the University of Adelaide. Before joining AIML, he was an Assistant Professor and later a tenured Associate Professor at Stony Brook University from 2014 to 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://gshoai.github.io
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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
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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.
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.
Europe PMC22022 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.
Scopus6 WoS5 Europe PMC32021 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).
Europe PMC32021 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.
Scopus12 WoS5 Europe PMC52021 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.
Scopus14 WoS82021 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.
Scopus7 WoS12 Europe PMC12021 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.
Scopus3 WoS12021 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.
Scopus6 WoS4 Europe PMC12020 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.
Scopus39 WoS35 Europe PMC282018 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.
Scopus5 WoS52018 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.
Scopus8 WoS52018 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.
Scopus116 WoS83 Europe PMC72014 Hoai, M., & De La Torre, F. (2014). Max-margin early event detectors. International Journal of Computer Vision, 107(2), 191-202.
Scopus170 WoS1412014 Hoai, M., Torresani, L., De La Torre, F., & Rother, C. (2014). Learning discriminative localization from weakly labeled data. Pattern Recognition, 47(3), 1523-1534.
Scopus31 WoS302010 Nguyen, M. H., & De La Torre, F. (2010). Metric learning for image alignment. International Journal of Computer Vision, 88(1), 69-84.
Scopus15 WoS112010 Nguyen, M. H., & de la Torre, F. (2010). Optimal feature selection for support vector machines. Pattern Recognition, 43(3), 584-591.
Scopus190 WoS1481988 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. -
Conference Papers
Year Citation 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).
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.
Scopus12023 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.
Scopus12023 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.
Scopus22023 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). CANADA, Vancouver: IEEE COMPUTER SOC.
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.
Scopus2 WoS12023 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.
Scopus22023 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). PEOPLES R CHINA, Macao: SPRINGER INTERNATIONAL PUBLISHING AG.
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). PEOPLES R CHINA, Macao: SPRINGER INTERNATIONAL PUBLISHING AG.
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.
Scopus1 WoS12022 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.
Scopus8 WoS22022 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.
Scopus1 WoS12022 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.
Scopus5 WoS12022 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.
Scopus32022 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.
Scopus32022 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.
Scopus7 WoS32021 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). ELECTR NETWORK: IEEE COMPUTER SOC.
Scopus23 WoS202021 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). ELECTR NETWORK: IEEE.
Scopus6 WoS62021 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). ELECTR NETWORK: IEEE COMPUTER SOC.
Scopus45 WoS192021 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.
Scopus30 WoS182021 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). ELECTR NETWORK: IEEE COMPUTER SOC.
Scopus13 WoS92021 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). ELECTR NETWORK: IEEE COMPUTER SOC.
Scopus3 WoS12021 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). ELECTR NETWORK: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
Scopus61 WoS332021 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). ELECTR NETWORK: IEEE.
Scopus32021 Ho, L. N., Tran, A. T., Phung, Q., & Hoai, M. (2021). 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). ELECTR NETWORK: IEEE.
Scopus7 WoS12021 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). ELECTR NETWORK: IEEE COMPUTER SOC.
Scopus37 WoS252021 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). ELECTR NETWORK: IEEE COMPUTER SOC.
Scopus57 WoS312021 Zhang, Z., Koraishy, F. M., & Hoai, M. (2021). Exemplar-Based Early Event Prediction in Video. In 32nd British Machine Vision Conference, BMVC 2021. 2021 Ranjan, V., Wang, B., Shah, M., & Hoai, M. (2021). 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). Springer International Publishing.
Scopus42020 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). IEEE.
Scopus302020 Wang, Y., Tran, V., Bertasius, G., Torresani, L., & Hoai, M. (2020). Attentive Action and Context Factorization. In 31st British Machine Vision Conference, BMVC 2020.
Scopus32020 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).
Scopus22020 Wang, B., Liu, H., Samaras, D., & Hoai, M. (2020). Distribution matching for crowd counting. In Advances in Neural Information Processing Systems Vol. 2020-December.
Scopus1382020 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.
Scopus212020 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). ELECTR NETWORK: IEEE.
Scopus36 WoS32 Europe PMC52020 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.
Scopus62020 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). ELECTR NETWORK: IEEE.
Scopus10 WoS32019 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.
Scopus26 WoS142019 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.
Scopus42 WoS252019 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.
Scopus10 WoS72019 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.
WoS12018 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).
Scopus92018 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.
Scopus65 WoS432018 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.
Scopus202018 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.
Scopus4 WoS32018 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.
Scopus67 WoS1722018 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.
WoS2102018 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.
Scopus21 WoS622018 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.
Scopus10 WoS32017 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.
Scopus164 WoS1222017 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.
Scopus39 WoS292017 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.
Scopus152016 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.
Scopus14 WoS62016 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.
Scopus30 WoS192016 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.
Scopus139 WoS1152016 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.
Scopus22 WoS122016 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.
Scopus82016 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 WoS12015 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.
Scopus1 WoS22015 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.
Scopus41 WoS292015 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.
Scopus25 WoS192015 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.
Scopus52014 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.
Scopus45 WoS202014 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. British Machine Vision Association.
Scopus132014 Hoai, M. (2014). Regularized Max Pooling for image categorization. In BMVC 2014 - Proceedings of the British Machine Vision Conference 2014. British Machine Vision Association.
Scopus512013 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.
Scopus41 WoS212012 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.
Scopus121 WoS562012 Hoai, M., & De La Torre, F. (2012). Maximum margin temporal clustering. In Journal of Machine Learning Research Vol. 22 (pp. 520-528).
Scopus202011 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.
Scopus204 WoS242010 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.
Scopus662009 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. IEEE.
Scopus3492009 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).
Scopus402009 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.
Scopus144 WoS852008 Nguyen, M. H., & De la Torre, F. (2008). Local minima free parameterized appearance models. In 2008 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-12 (pp. 1412-1419). AK, Anchorage: IEEE. 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.
Scopus82008 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.
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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
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