139 citations · 717 across the 57 of their papers we have counts for
11 papers · 1 filter
Compact Trilinear Interaction for Visual Question Answering
Tuong Do, Thanh-Toan Do, Huy Tran +2
In Visual Question Answering (VQA), answers have a great correlation with question meaning and visual contents. Thus, to selectively utilize image, question and answer information,…
Overcoming Data Limitation in Medical Visual Question Answering
Binh D. Nguyen, Thanh-Toan Do, Binh X. Nguyen +3
Traditional approaches for Visual Question Answering (VQA) require large amount of labeled data for training. Unfortunately, such large scale data is usually not available for medi…
Scalable Place Recognition Under Appearance Change for Autonomous Driving
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin +3
A major challenge in place recognition for autonomous driving is to be robust against appearance changes due to short-term (e.g., weather, lighting) and long-term (seasons, vegetat…
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
We introduce a new, rigorously-formulated Bayesian meta-learning algorithm that learns a probability distribution of model parameter prior for few-shot learning. The proposed algor…
Bayesian Generative Active Deep Learning
Toan Tran, Thanh-Toan Do, Ian Reid +1
Deep learning models have demonstrated outstanding performance in several problems, but their training process tends to require immense amounts of computational and human resources…
Simultaneous Feature Aggregating and Hashing for Compact Binary Code Learning
Thanh-Toan Do, Khoa Le, Tuan Hoang +3
Representing images by compact hash codes is an attractive approach for large-scale content-based image retrieval. In most state-of-the-art hashing-based image retrieval systems, f…
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
Thanh-Toan Do, Toan Tran, Ian Reid +3
We propose a method that substantially improves the efficiency of deep distance metric learning based on the optimization of the triplet loss function. One epoch of such training p…
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences
Huu Le, Thanh-Toan Do, Tuan Hoang +1
This paper presents a novel randomized algorithm for robust point cloud registration without correspondences. Most existing registration approaches require a set of putative corres…
V2CNet: A Deep Learning Framework to Translate Videos to Commands for Robotic Manipulation
Anh Nguyen, Thanh-Toan Do, Ian Reid +2
We propose V2CNet, a new deep learning framework to automatically translate the demonstration videos to commands that can be directly used in robotic applications. Our V2CNet has t…
SASSE: Scalable and Adaptable 6-DOF Pose Estimation
Huu Le, Tuan Hoang, Qianggong Zhang +3
Visual localization has become a key enabling component of many place recognition and SLAM systems. Contemporary research has primarily focused on improving accuracy and precision-…
Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes
Yu Liu, Lingqiao Liu, Hamid Rezatofighi +3
As the post-processing step for object detection, non-maximum suppression (GreedyNMS) is widely used in most of the detectors for many years. It is efficient and accurate for spars…