2020
Do, T. -T., Hoang, T., Le Tan, D. -K., Doan, A. -D., & Cheung, N. -M. (2020). Compact Hash Code Learning with Binary Deep Neural Network. IEEE Transactions on Multimedia, 22(4), 992-1004. doi:10.1109/TMM.2019.2935680DOI: 10.1109/TMM.2019.2935680
2019
Hoang, T., Do, T. -T., Le, H., Le-Tan, D. -K., & Cheung, N. -M. (2019). Simultaneous compression and quantization: A joint approach for efficient unsupervised hashing. Computer Vision and Image Understanding, 102852. doi:10.1016/j.cviu.2019.102852DOI: 10.1016/j.cviu.2019.102852
Nguyen, B. D., Do, T. -T., Nguyen, B. X., Do, T., Tjiputra, E., & Tran, Q. D. (2019). Overcoming Data Limitation in Medical Visual Question Answering. In Lecture Notes in Computer Science Vol. 11767 (pp. 522-530). Shenzhen, China: Springer International Publishing. doi:10.1007/978-3-030-32251-9_57DOI: 10.1007/978-3-030-32251-9_57
Le, H. M., Chin, T. -J., Eriksson, A., Do, T. -T., & Suter, D. (2019). Deterministic Approximate Methods for Maximum Consensus Robust Fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1. doi:10.1109/tpami.2019.2939307DOI: 10.1109/tpami.2019.2939307
Do, T. -T., Tran, T., Reid, I., Kumar, V., Hoang, T., & Carneiro, G. (2019). A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning. In 2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (pp. 10396-10405). doi:10.1109/CVPR.2019.01065DOI: 10.1109/CVPR.2019.01065
Thanh-Toan, D., Tuan, H., Dang-Khoa, L. T., Le, H., Nguyen, T. V., & Cheung, N. -M. (2019). From Selective Deep Convolutional Features to Compact Binary Representations for Image Retrieval. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 15(2). doi:10.1145/3314051DOI: 10.1145/3314051
Le, H., Eriksson, A., Do, T. -T., & Milford, M. (2019). A Binary Optimization Approach for Constrained K-Means Clustering. In Asian Conference on Computer Vision (ACCV).
Do, T. -T., Le, K., Hoang, T., Le, H., Nguyen, T. V., & Cheung, N. -M. (2019). Simultaneous Feature Aggregating and Hashing for Compact Binary Code Learning. IEEE Transactions on Image Processing, 28(10), 4954-4969. doi:10.1109/TIP.2019.2913509DOI: 10.1109/TIP.2019.2913509
Thanh-Toan, D., Tuan, H., Dang-Khoa, L. T., Trung, P., Huu, L., Cheung, N. -M., & Reid, I. (2019). Binary Constrained Deep Hashing Network for Image Retrieval without Manual Annotation. In 2019 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV) (pp. 695-704). doi:10.1109/WACV.2019.00079DOI: 10.1109/WACV.2019.00079
Tran, T., Do, T. T., Reid, I., & Carneiro, G. (2019). Bayesian generative active deep learning. In 36th International Conference on Machine Learning, ICML 2019 Vol. 2019-June (pp. 10969-10978).
2018
Tran, N. T., Le, D. K. T., Doan, A. D., Do, T. T., Bui, T. A., Tan, M., & Cheung, N. M. (2018). On-device Scalable Image-based Localization via Prioritized Cascade Search and Fast One-Many RANSAC.. IEEE Transactions on Image Processing.
Accessible Melanoma Detection Using Smartphones and Mobile Image Analysis (Journal article)
Do, T. -T., Hoang, T., Pomponiu, V., Zhou, Y., Chen, Z., Cheung, N. -M., . . . Tan, S. -H. (2018). Accessible Melanoma Detection Using Smartphones and Mobile Image Analysis. IEEE Transactions on Multimedia, 20(10), 2849-2864. doi:10.1109/tmm.2018.2814346DOI: 10.1109/tmm.2018.2814346
Supervised Hashing with End-to-End Binary Deep Neural Network (Conference Paper)
Tan, D. -K. L., Do, T. -T., & Cheung, N. -M. (2018). Supervised Hashing with End-to-End Binary Deep Neural Network. In IEEE International Conference on Image Processing.
Improving Chamfer Template Matching Using Image Segmentation (Journal article)
Nguyen, D. T., Vu, N. -S., Do, T. -T., Nguyen, T., & Yearwood, J. (2018). Improving Chamfer Template Matching Using Image Segmentation. IEEE Signal Processing Letters, 25, 1635-1639.
SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes (Conference Paper)
Pham, T., Do, T. -T., Sünderhauf, N., & Reid, I. (2018). SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes. In International Conference on Robotics and Automation (ICRA).
Embedding based on function approximation for large scale image search (Journal article)
Do, T. -T., & Cheung, N. -M. (2018). Embedding based on function approximation for large scale image search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(3), 626-638. doi:10.1109/TPAMI.2017.2686861DOI: 10.1109/TPAMI.2017.2686861
Bayesian Instance Segmentation in Open Set World (Conference Paper)
Pham, T., Kumar, B. G., Do, T. -T., Carneiro, G., Reid, I., & others. (2018). Bayesian Instance Segmentation in Open Set World. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 3-18).
DeepVQ: A Deep Network Architecture for Vector Quantization (Conference Paper)
Le Tan, D. -K., Le, H., Hoang, T., Do, T. -T., & Cheung, N. -M. (2018). DeepVQ: A Deep Network Architecture for Vector Quantization. In CVPR Workshops, 2018 (pp. 2579-2582).
Non-smooth M-estimator for Maximum Consensus Estimation (Conference Paper)
Le, H., Eriksson, A., Milford, M., Do, T. -T., Chin, T. -J., & Suter, D. (2018). Non-smooth M-estimator for Maximum Consensus Estimation. In British Machine Vision Conference (BMVC).
Real-time Monocular Object Instance 6D Pose Estimation (Conference Paper)
Do, T. -T., Pham, T., Cai, M., & Reid, I. (2018). Real-time Monocular Object Instance 6D Pose Estimation. In British Machine Vision Conference (BMVC).
2017
Enhancing feature discrimination for unsupervised hashing (Conference Paper)
Hoang, T., Do, T. -T., Le Tan, D. -K., & Cheung, N. -M. (2017). Enhancing feature discrimination for unsupervised hashing. In IEEE International Conference on Image Processing (pp. 3710-3714).
AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection (Conference Paper)
Thanh-Toan, D., Anh, N., & Reid, I. (2018). AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection. In 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA) (pp. 5882-5889). Retrieved from https://www.webofscience.com/
Method and device for analysing an image (Patent)
Do, T. -T., Zhou, Y., Pomponiu, V., Cheung, N. -M., & Koh, D. C. I. (2017). Method and device for analysing an image.
MediaEval 2017 Predicting Media Interestingness Task (Conference Paper)
Demarty, C. -H., Sjöberg, M., Ionescu, B., Do, T. -T., Gygli, M., & Duong, N. Q. K. (2017). MediaEval 2017 Predicting Media Interestingness Task. In MediaEval Workshop.
Predicting Interestingness of Visual Content (Chapter)
Demarty, C. -H., Sjöberg, M., Constantin, M. G., Duong, N. Q. K., Ionescu, B., Do, T. -T., & Wang, H. (2017). Predicting Interestingness of Visual Content. In Visual Content Indexing and Retrieval with Psycho-Visual Models (pp. 233-265). Springer, Cham.
Selective deep convolutional features for image retrieval (Conference Paper)
Hoang, T., Do, T. -T., Le Tan, D. -K., & Cheung, N. -M. (2017). Selective deep convolutional features for image retrieval. In Proceedings of the 2017 ACM on Multimedia Conference (pp. 1600-1608). ACM.
Simultaneous feature aggregating and hashing for large-scale image search (Conference Paper)
Do, T. -T., Tan, D. -K. L., Pham, T. T., & Cheung, N. -M. (2017). Simultaneous feature aggregating and hashing for large-scale image search. In IEEE Computer Vision and Pattern Recognition (CVPR).
2016
Computation and Memory Efficient Image Segmentation (Journal article)
Zhou, Y., Do, T. -T., Zheng, H., Cheung, N. -M., & Fang, L. (n.d.). Computation and Memory Efficient Image Segmentation. IEEE Transactions on Circuits and Systems for Video Technology.
Smartphone and Mobile Image Processing for Assisted Living: Health-monitoring apps powered by advanced mobile imaging algorithms (Journal article)
Nejati, H., Pomponiu, V., Do, T. -T., Zhou, Y., Iravani, S., & Cheung, N. -M. (2016). Smartphone and Mobile Image Processing for Assisted Living: Health-monitoring apps powered by advanced mobile imaging algorithms. IEEE Signal Processing Magazine, 33(4), 30-48. doi:10.1109/msp.2016.2549996DOI: 10.1109/msp.2016.2549996
Binary hashing with semidefinite relaxation and augmented lagrangian (Conference Paper)
Do, T. -T., Doan, A. -D., Nguyen, D. -T., & Cheung, N. -M. (2016). Binary hashing with semidefinite relaxation and augmented lagrangian. In European Conference on Computer Vision (pp. 802-817). Springer, Cham.
Image-based vehicle analysis using deep neural network: A systematic study (Conference Paper)
Zhou, Y., Nejati, H., Do, T. -T., Cheung, N. -M., & Cheah, L. (2016). Image-based vehicle analysis using deep neural network: A systematic study. In Digital Signal Processing (DSP), 2016 IEEE International Conference on (pp. 276-280). IEEE.
Learning to hash with binary deep neural network (Conference Paper)
Do, T. -T., Doan, A. -D., & Cheung, N. -M. (2016). Learning to hash with binary deep neural network. In European Conference on Computer Vision (pp. 219-234). Springer, Cham.
2015
Designing a mobile imaging system for early melanoma detection (Journal article)
Thanh-Toan Do, S. S. (2015). Designing a mobile imaging system for early melanoma detection. JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY.
Do, T. -T., Tran, Q. D., & Cheung, N. -M. (2015). FAemb: a function approximation-based embedding method for image retrieval. In CVPR, 2015 (pp. 3556-3564).
2014
Early melanoma diagnosis with mobile imaging (Conference Paper)
Do, T., Zhou, Y., Zheng, H., Cheung, N. -M., & Koh, D. (2014). Early melanoma diagnosis with mobile imaging. In IEEE Engineering in Medicine and Biology Society.
2012
Enlarging hacker’s toolbox: deluding image recognition by attacking keypoint orientations (Conference Paper)
Do, T. -T., Kijak, E., Amsaleg, L., & Furon, T. (2012). Enlarging hacker’s toolbox: deluding image recognition by attacking keypoint orientations. In Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on (pp. 1817-1820). IEEE.
Face recognition using co-occurrence histograms of oriented gradients (Conference Paper)
Do, T. -T., & Kijak, E. (2012). Face recognition using co-occurrence histograms of oriented gradients. In Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on (pp. 1301-1304). IEEE.
Security-oriented picture-in-picture visual modifications (Conference Paper)
Do, T. -T., Kijak, E., Amsaleg, L., & Furon, T. (2012). Security-oriented picture-in-picture visual modifications. In Proceedings of the 2nd ACM International Conference on Multimedia Retrieval (pp. 13). ACM.
2010
Challenging the security of content-based image retrieval systems (Conference Paper)
Do, T. -T., Kijak, E., Furon, T., & Amsaleg, L. (2010). Challenging the security of content-based image retrieval systems. In Multimedia Signal Processing (MMSP), 2010 IEEE International Workshop on (pp. 52-57). IEEE.
Deluding image recognition in SIFT-based CBIR systems (Conference Paper)
Do, T. -T., Kijak, E., Furon, T., & Amsaleg, L. (2010). Deluding image recognition in SIFT-based CBIR systems. In Proceedings of the 2nd ACM workshop on Multimedia in forensics, security and intelligence (pp. 7-12). ACM.
Understanding the security and robustness of SIFT (Conference Paper)
Do, T. -T., Kijak, E., Furon, T., & Amsaleg, L. (2010). Understanding the security and robustness of SIFT. In Proceedings of the 18th ACM international conference on Multimedia (pp. 1195-1198). ACM.
