14 citations · 48 across the 17 of their papers we have counts for
20 papers
Controllable Group Choreography using Contrastive Diffusion
Nhat Le, Tuong Do, Khoa Do +4
Music-driven group choreography poses a considerable challenge but holds significant potential for a wide range of industrial applications. The ability to generate synchronized and…
Music-Driven Group Choreography
Nhat Le, Thang Pham, Tuong Do +3
Music-driven choreography is a challenging problem with a wide variety of industrial applications. Recently, many methods have been proposed to synthesize dance motions from music…
Style Transfer for 2D Talking Head Animation
Trong-Thang Pham, Nhat Le, Tuong Do +4
Audio-driven talking head animation is a challenging research topic with many real-world applications. Recent works have focused on creating photo-realistic 2D animation, while lea…
Reducing Non-IID Effects in Federated Autonomous Driving with Contrastive Divergence Loss
Tuong Do, Binh X. Nguyen, Hien Nguyen +4
Federated learning has been widely applied in autonomous driving since it enables training a learning model among vehicles without sharing users' data. However, data from autonomou…
Uncertainty-aware Label Distribution Learning for Facial Expression Recognition
Nhat Le, Khanh Nguyen, Quang Tran +3
Despite significant progress over the past few years, ambiguity is still a key challenge in Facial Expression Recognition (FER). It can lead to noisy and inconsistent annotation, w…
Reducing Training Time in Cross-Silo Federated Learning using Multigraph Topology
Tuong Do, Binh X. Nguyen, Vuong Pham +4
Federated learning is an active research topic since it enables several participants to jointly train a model without sharing local data. Currently, cross-silo federated learning i…
Fine-Grained Visual Classification using Self Assessment Classifier
Tuong Do, Huy Tran, Erman Tjiputra +2
Extracting discriminative features plays a crucial role in the fine-grained visual classification task. Most of the existing methods focus on developing attention or augmentation m…
Light-weight Deformable Registration using Adversarial Learning with Distilling Knowledge
Minh Q. Tran, Tuong Do, Huy Tran +3
Deformable registration is a crucial step in many medical procedures such as image-guided surgery and radiation therapy. Most recent learning-based methods focus on improving the a…
Deep Federated Learning for Autonomous Driving
Anh Nguyen, Tuong Do, Minh Tran +5
Autonomous driving is an active research topic in both academia and industry. However, most of the existing solutions focus on improving the accuracy by training learnable models w…
Coarse-to-Fine Reasoning for Visual Question Answering
Binh X. Nguyen, Tuong Do, Huy Tran +3
Bridging the semantic gap between image and question is an important step to improve the accuracy of the Visual Question Answering (VQA) task. However, most of the existing VQA met…
Fine-grained Hand Gesture Recognition in Multi-viewpoint Hand Hygiene
Huy Q. Vo, Tuong Do, Vi C. Pham +3
This paper contributes a new high-quality dataset for hand gesture recognition in hand hygiene systems, named "MFH". Generally, current datasets are not focused on: (i) fine-graine…
Multiple Meta-model Quantifying for Medical Visual Question Answering
Tuong Do, Binh X. Nguyen, Erman Tjiputra +3
Transfer learning is an important step to extract meaningful features and overcome the data limitation in the medical Visual Question Answering (VQA) task. However, most of the exi…
Graph-based Person Signature for Person Re-Identifications
Binh X. Nguyen, Binh D. Nguyen, Tuong Do +3
The task of person re-identification (ReID) is to match images of the same person over multiple non-overlapping camera views. Due to the variations in visual factors, previous work…
Autonomous Navigation with Mobile Robots using Deep Learning and the Robot Operating System
Anh Nguyen, Quang Tran
Autonomous navigation is a long-standing field of robotics research, which provides an essential capability for mobile robots to execute a series of tasks on the same environments…
Multiple interaction learning with question-type prior knowledge for constraining answer search space in visual question answering
Tuong Do, Binh X. Nguyen, Huy Tran +3
Different approaches have been proposed to Visual Question Answering (VQA). However, few works are aware of the behaviors of varying joint modality methods over question type prior…
Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding
Binh X. Nguyen, Binh D. Nguyen, Gustavo Carneiro +3
Unsupervised Deep Distance Metric Learning (UDML) aims to learn sample similarities in the embedding space from an unlabeled dataset. Traditional UDML methods usually use the tripl…
Autonomous Navigation in Complex Environments with Deep Multimodal Fusion Network
Anh Nguyen, Ngoc Nguyen, Kim Tran +2
Autonomous navigation in complex environments is a crucial task in time-sensitive scenarios such as disaster response or search and rescue. However, complex environments pose signi…
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…
Object Captioning and Retrieval with Natural Language
Anh Nguyen, Thanh-Toan Do, Ian Reid +2
We address the problem of jointly learning vision and language to understand the object in a fine-grained manner. The key idea of our approach is the use of object descriptions to…