449 citations · 492 across the 14 of their papers we have counts for
17 papers
MVC: A Multi-Task Vision Transformer Network for COVID-19 Diagnosis from Chest X-ray Images
Huyen Tran, Duc Thanh Nguyen, John Yearwood
Medical image analysis using computer-based algorithms has attracted considerable attention from the research community and achieved tremendous progress in the last decade. With re…
Causal Inference via Style Transfer for Out-of-distribution Generalisation
Toan Nguyen, Kien Do, Duc Thanh Nguyen +2
Out-of-distribution (OOD) generalisation aims to build a model that can generalise well on an unseen target domain using knowledge from multiple source domains. To this end, the mo…
PointInverter: Point Cloud Reconstruction and Editing via a Generative Model with Shape Priors
Jaeyeon Kim, Binh-Son Hua, Duc Thanh Nguyen +1
In this paper, we propose a new method for mapping a 3D point cloud to the latent space of a 3D generative adversarial network. Our generative model for 3D point clouds is based on…
RFNet-4D++: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds with Cross-Attention Spatio-Temporal Features
Tuan-Anh Vu, Duc Thanh Nguyen, Binh-Son Hua +2
Object reconstruction from 3D point clouds has been a long-standing research problem in computer vision and computer graphics, and achieved impressive progress. However, reconstruc…
Minimal Adversarial Examples for Deep Learning on 3D Point Clouds
Jaeyeon Kim, Binh-Son Hua, Duc Thanh Nguyen +1
With recent developments of convolutional neural networks, deep learning for 3D point clouds has shown significant progress in various 3D scene understanding tasks, e.g., object re…
Meta Transfer Learning for Emotion Recognition
Dung Nguyen, Sridha Sridharan, Duc Thanh Nguyen +3
Deep learning has been widely adopted in automatic emotion recognition and has lead to significant progress in the field. However, due to insufficient annotated emotion datasets, p…
Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition
Dung Nguyen, Duc Thanh Nguyen, Rui Zeng +5
Multimodal dimensional emotion recognition has drawn a great attention from the affective computing community and numerous schemes have been extensively investigated, making a sign…
Joint Deep Cross-Domain Transfer Learning for Emotion Recognition
Dung Nguyen, Sridha Sridharan, Duc Thanh Nguyen +4
Deep learning has been applied to achieve significant progress in emotion recognition. Despite such substantial progress, existing approaches are still hindered by insufficient tra…
SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information
Jing Yu Koh, Duc Thanh Nguyen, Quang-Trung Truong +2
Fully-automatic execution is the ultimate goal for many Computer Vision applications. However, this objective is not always realistic in tasks associated with high failure costs, s…
LCD: Learned Cross-Domain Descriptors for 2D-3D Matching
Quang-Hieu Pham, Mikaela Angelina Uy, Binh-Son Hua +3
In this work, we present a novel method to learn a local cross-domain descriptor for 2D image and 3D point cloud matching. Our proposed method is a dual auto-encoder neural network…
Deep Learning for Deepfakes Creation and Detection: A Survey
Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen +6
Deep learning has been successfully applied to solve various complex problems ranging from big data analytics to computer vision and human-level control. Deep learning advances how…
Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data
Mikaela Angelina Uy, Quang-Hieu Pham, Binh-Son Hua +2
Deep learning techniques for point cloud data have demonstrated great potentials in solving classical problems in 3D computer vision such as 3D object classification and segmentati…
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields
Quang-Hieu Pham, Duc Thanh Nguyen, Binh-Son Hua +2
Deep learning techniques have become the to-go models for most vision-related tasks on 2D images. However, their power has not been fully realised on several tasks in 3D space, e.g…
Machine learning for the recognition of emotion in the speech of couples in psychotherapy using the Stanford Suppes Brain Lab Psychotherapy Dataset
Colleen E. Crangle, Rui Wang, Marcos Perreau-Guimaraes +3
The automatic recognition of emotion in speech can inform our understanding of language, emotion, and the brain. It also has practical application to human-machine interactive syst…
Real-time Progressive 3D Semantic Segmentation for Indoor Scene
Quang-Hieu Pham, Binh-Son Hua, Duc Thanh Nguyen +1
The widespread adoption of autonomous systems such as drones and assistant robots has created a need for real-time high-quality semantic scene segmentation. In this paper, we propo…
A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation
Duc Thanh Nguyen, Binh-Son Hua, Lap-Fai Yu +1
Recent advances of 3D acquisition devices have enabled large-scale acquisition of 3D scene data. Such data, if completely and well annotated, can serve as useful ingredients for a…
Binary Hashing with Semidefinite Relaxation and Augmented Lagrangian
Thanh-Toan Do, Anh-Dzung Doan, Duc-Thanh Nguyen +1
This paper proposes two approaches for inferencing binary codes in two-step (supervised, unsupervised) hashing. We first introduce an unified formulation for both supervised and un…