Duc Thanh Nguyen
Bsc (HCMCUS), Msc (AIT), PhD (UOW)
I am currently a Senior Lecturer at the School of Information Technology, Deakin University. I was a postdoctoral research fellow at SUTD and a researcher at the School of Computer Science and Software Engineering and Smart Food Centre, School of Medicine, University of Wollongong.
My profile: CV, Google Scholar
If you are interested in doing PhD in Computer Vision, please send me your resume and research topic (at email@example.com)
- Image Processing and Computer Vision: Human and object detection, statistical approaches for object detection and segmentation, shape analysis, visual feature extraction
- Machine Learning and Pattern Recognition: Multi-instance multi-label learning, graphical models for machine learning, variational methods, statistical machine learning and pattern recognition
- Multimedia Signal Processing: Video analysis, image and video retrieval
- Document Image Analysis and OCR: Page segmentation, text extraction, document skew estimation, document binarisation
- Artificial Intelligence: Scheduling and genetic algorithms
- Nov 15, 2020: I will serve as an Area Chair for the subject area "Multimedia Analysis and Understanding" of the IEEE International Conference on Multimedia and Expo (ICME) 2021 (http://2021.ieeeicme.org).
- Oct 26, 2020: I have been recognised as an outstanding reviewer for ECCV 2020.
- Oct 5, 2020: Our paper "A graph-based for population health analysis using geo-tagged tweets" has been accepted for publication in Multimedia Tools and Applications.
- Jul 3, 2020: Our paper "SideInfNet: a deep neural network for semantic segmentation with side information" has been accepted in ECCV 2020.
- Nov 11, 2019: Our paper "A deep cross-domain descriptor for 2D-3D matching" has been accepted in AAAI 2020 (oral).
- Jul 23, 2019: Our paper "Revisiting point cloud classification: a new benchmark dataset and classification model on real-world data" has been accepted in ICCV 2019 (oral - 4.3%).
- Mar 2, 2019: Our paper "JSIS3D: Joint semantic-instance segmentation of 3D point clouds with multi-task pointwise networks and multi-value conditional random fields" has been accepted in CVPR 2019 (oral - 5.6%). The paper can be found at openaccess.thecvf.com/content_CVPR_2019/papers/Pham_JSIS3D_Joint_Semantic-Instance_Segmentation_of_3D_Point_Clouds_With_Multi-Task_CVPR_2019_paper.pdf
- Nov 8, 2018: Our paper "Real-time progressive 3D semantic segmentation for indoor scenes" has been accepted in WACV 2019.
- Nov 6, 2018: Our grant application "A large-scale and fine-grained dataset for detection and recognition of animals in the wild" (~ $14,000) has been successful (funded by Deakin University).
- Jul 13, 2018: Our paper "Improving Chamfer template matching using image segmentation" has been accepted in IEEE Signal Processing Letters.
- Jul 3, 2018: Our paper "Urban zoning using higher-order Markov random fields on multi-view imagery data" has been accepted in ECCV 2018. The paper can be found at openaccess.thecvf.com/content_ECCV_2018/papers/Tian_Feng_Urban_Zoning_Using_ECCV_2018_paper.pdf.
- Jan 5, 2018: Our paper "Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices" has been accepted in Future Generation Computer Systems.
- Dec 1, 2017: Our tutorial proposal on "Creating annotated scene meshes for training and testing robot systems" has been accepted for the 2018 IEEE International Conference on Robotics and Automation, Brisbane. The tutorial homepage can be found at http://220.127.116.11:8080/scenenn/dev/icra18/. An early WebGL demo can be found at http://18.104.22.168:8080/scenenn/dev/icra18/WebGLApp/.
- Aug 8, 2017: Our paper "Detection of ground parrot vocalisations: a multiple instance learning approach" has been accepted in Journal of Acoustical Society of America.
- Aug 4, 2017: Our paper "A robust 3D-2D interactive tool for scene segmentation and annotation" has been accepted in IEEE Transactions on Visualization and Computer Graphics. The tool will be published soon.
- Jul 1, 2017: Our paper "Kernel-based features for predicting population health indices from geocoded social media data" has been accepted in Decision Support Systems.
- Mar 21, 2017: Our paper "SHREC'17: RGB-D to CAD retrieval with ObjectNN dataset" has been accepted and will appear in the 3D Object Retrieval workshop (3DOR), Eurographics 2017. Details can be found at http://people.sutd.edu.sg/~saikit/projects/sceneNN/shrec17/
- Feb 6, 2017: Our paper "Prediction of population health indices from social media using kernel-based textual and temporal features" has been accepted in the 26th ACM World Wide Web - WWW, 2017 (Cognitive Computing Alternative Research Track).
- Feb 1, 2017: Our grant application "Data-driven approaches for 3D modeling in graphics and vision" (~ $500,000 SGD) has been successful (funded by the Ministry of Education of Singapore).
- Jan 16, 2017: I am a member of the advisory board of the SHREC2017 - 3D Shape Retrieval Contest: RGB-D Object-to-CAD Retrieval track (12th Eurographics 2017 Workshop on 3D Object Retrieval). Details can be found at http://people.sutd.edu.sg/~saikit/projects/sceneNN/shrec17/
- Jan 13, 2017: Our grant application "A multi-source semantic 3D modeling platform for virtual Singapore" (~ $750,000 SGD) has been successful (funded by the National Research Foundation of Singapore).
- Oct 29, 2016: Our paper "SceneNN: a scene meshes dataset with annotations" has been awarded Best Paper Honorable Mention in 3DV 2016 (http://3dv.stanford.edu/). Congratulations team!
- Oct 20, 2016: Our paper "A robust 3D-2D interactive tool for scene segmentation and annotation" is now available at http://arxiv.org/abs/1610.05883
- SIT112: Data science concepts
- SIT199: Applied algebra and statistics
- SIT205: Thinking systems and cognitive science (Lecturing + Unit chair)
- SIT221: Data structures and algorithms (Lecturing + Unit chair)
- SIT232/771: Object-oriented development (Lecturing + Unit chair)
- SIT773: Software requirements analysis and modelling (Lecturing + Unit chair)
Honours and Awards
- Best Paper Honorable Mention for the work "SceneNN: a scene meshes dataset with annotations" (sponsored by Facebook) in the 2016 IEEE International Conference on 3D Computer Vision (3DV)
- Young Researcher Support granted by the 2014 IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2014)
- Travel Grant to the 2011 IEEE International Conference on Image Processing (ICIP 2011)
- Full scholarship offered by the University of Wollongong, Australia for Ph.D. study in Computer Science, 2008.
- Full scholarship offered by the National University of Singapore (NUS) for Ph.D. study (Computer Science/School of Computing), 2008
- Full scholarship offered by the Ministry of Education and Training (MOET) of Vietnam for Master study in Computer Science, 2004
Hung Nguyen, PhD (2020)
- Thesis: Machine learning approaches for population health analytics through social media
- Organizer of the tutorial on "Creating Annotated Scene Meshes for Training and Testing Robot Systems", 2018 IEEE International Conference on Robotics and Automation, Brisbane. The tutorial homepage can be found at http://22.214.171.124:8080/scenenn/dev/icra18/. An early WebGL demo can be found at http://126.96.36.199:8080/scenenn/dev/icra18/WebGLApp/.
- Member of Advisory board of the 2017 Eurographics Workshop on 3D Object Retrieval (http://people.sutd.edu.sg/~saikit/projects/sceneNN/shrec17/index.html)
- Scientific Reports/Nature
- Pattern Recognition
- IEEE Transactions on Image Processing
- IEEE Transactions on Intelligent Transportation Systems
- IEEE Signal Processing Letters
- Image and Vision Computing
- Pattern Recognition Letters
- Journal of Visual Communication and Image Representation
- IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
- IEEE International Conference on Computer Vision (ICCV)
- European Conference on Computer Vision (ECCV)
- AAAI Conference on Artificial Inteligence (AAAI)
- Siggraph Asia
- IEEE International Conference on Image Processing (ICIP)
- Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
- ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2008)