14 citations · 38 across the 22 of their papers we have counts for
24 papers
Efficient Human-Contact Representation for Human-Scene Interaction
Nghia Vu, Tuong Do, Binh X. Nguyen +2
Human-scene interaction is an active research topic with several industrial applications in virtual reality, gaming, robotics, and surveillance. Despite significant progress in net…
AeroScene: Progressive Scene Synthesis for Aerial Robotics
Nghia Vu, Tuong Do, Dzung Tran +6
Generative models have shown substantial impact across multiple domains, their potential for scene synthesis remains underexplored in robotics. This gap is more evident in drone si…
AffordMatcher: Affordance Learning in 3D Scenes from Visual Signifiers
Nghia Vu, Tuong Do, Khang Nguyen +8
Affordance learning is a complex challenge in many applications, where existing approaches primarily focus on the geometric structures, visual knowledge, and affordance labels of o…
Lightweight Temporal Transformer Decomposition for Federated Autonomous Driving
Tuong Do, Binh X. Nguyen, Quang D. Tran +3
Traditional vision-based autonomous driving systems often face difficulties in navigating complex environments when relying solely on single-image inputs. To overcome this limitati…
FedEFM: Federated Endovascular Foundation Model with Unseen Data
Tuong Do, Nghia Vu, Tudor Jianu +7
In endovascular surgery, the precise identification of catheters and guidewires in X-ray images is essential for reducing intervention risks. However, accurately segmenting cathete…
SplineFormer: An Explainable Transformer-Based Approach for Autonomous Endovascular Navigation
Tudor Jianu, Shayan Doust, Mengyun Li +8
Endovascular navigation is a crucial aspect of minimally invasive procedures, where precise control of curvilinear instruments like guidewires is critical for successful interventi…
Guide3D: A Bi-planar X-ray Dataset for 3D Shape Reconstruction
Tudor Jianu, Baoru Huang, Hoan Nguyen +8
Endovascular surgical tool reconstruction represents an important factor in advancing endovascular tool navigation, which is an important step in endovascular surgery. However, the…
CathAction: A Benchmark for Endovascular Intervention Understanding
Baoru Huang, Tuan Vo, Chayun Kongtongvattana +35
Real-time visual feedback from catheterization analysis is crucial for enhancing surgical safety and efficiency during endovascular interventions. However, existing datasets are of…
Scalable Group Choreography via Variational Phase Manifold Learning
Nhat Le, Khoa Do, Xuan Bui +4
Generating group dance motion from the music is a challenging task with several industrial applications. Although several methods have been proposed to tackle this problem, most of…
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…
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…
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…
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…