753 citations · 1.1k across the 27 of their papers we have counts for
28 papers
Few-Shot Object Detection via Synthetic Features with Optimal Transport
Anh-Khoa Nguyen Vu, Thanh-Toan Do, Vinh-Tiep Nguyen +3
Few-shot object detection aims to simultaneously localize and classify the objects in an image with limited training samples. However, most existing few-shot object detection metho…
DM-VTON: Distilled Mobile Real-time Virtual Try-On
Khoi-Nguyen Nguyen-Ngoc, Thanh-Tung Phan-Nguyen, Khanh-Duy Le +3
The fashion e-commerce industry has witnessed significant growth in recent years, prompting exploring image-based virtual try-on techniques to incorporate Augmented Reality (AR) ex…
VIDES: Virtual Interior Design via Natural Language and Visual Guidance
Minh-Hien Le, Chi-Bien Chu, Khanh-Duy Le +3
Interior design is crucial in creating aesthetically pleasing and functional indoor spaces. However, developing and editing interior design concepts requires significant time and e…
CamoFA: A Learnable Fourier-based Augmentation for Camouflage Segmentation
Minh-Quan Le, Minh-Triet Tran, Trung-Nghia Le +2
Camouflaged object detection (COD) and camouflaged instance segmentation (CIS) aim to recognize and segment objects that are blended into their surroundings, respectively. While se…
Instance-level Few-shot Learning with Class Hierarchy Mining
Anh-Khoa Nguyen Vu, Thanh-Toan Do, Nhat-Duy Nguyen +3
Few-shot learning is proposed to tackle the problem of scarce training data in novel classes. However, prior works in instance-level few-shot learning have paid less attention to e…
The Art of Camouflage: Few-Shot Learning for Animal Detection and Segmentation
Thanh-Danh Nguyen, Anh-Khoa Nguyen Vu, Nhat-Duy Nguyen +5
Camouflaged object detection and segmentation is a new and challenging research topic in computer vision. There is a serious issue of lacking data on concealed objects such as camo…
MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation
Minh-Quan Le, Tam V. Nguyen, Trung-Nghia Le +3
Few-shot instance segmentation extends the few-shot learning paradigm to the instance segmentation task, which tries to segment instance objects from a query image with a few annot…
Multi-Modal Mutual Information Maximization: A Novel Approach for Unsupervised Deep Cross-Modal Hashing
Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen +1
In this paper, we adopt the maximizing mutual information (MI) approach to tackle the problem of unsupervised learning of binary hash codes for efficient cross-modal retrieval. We…
GUNNEL: Guided Mixup Augmentation and Multi-Model Fusion for Aquatic Animal Segmentation
Minh-Quan Le, Trung-Nghia Le, Tam V. Nguyen +2
Recent years have witnessed great advances in object segmentation research. In addition to generic objects, aquatic animals have attracted research attention. Deep learning-based m…
Contextual Guided Segmentation Framework for Semi-supervised Video Instance Segmentation
Trung-Nghia Le, Tam V. Nguyen, Minh-Triet Tran
In this paper, we propose Contextual Guided Segmentation (CGS) framework for video instance segmentation in three passes. In the first pass, i.e., preview segmentation, we propose…
Anabranch Network for Camouflaged Object Segmentation
Trung-Nghia Le, Tam V. Nguyen, Zhongliang Nie +2
Camouflaged objects attempt to conceal their texture into the background and discriminating them from the background is hard even for human beings. The main objective of this paper…
Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite
Trung-Nghia Le, Yubo Cao, Tan-Cong Nguyen +5
This paper pushes the envelope on decomposing camouflaged regions in an image into meaningful components, namely, camouflaged instances. To promote the new task of camouflaged inst…
Unsupervised Deep Cross-modality Spectral Hashing
Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen +1
This paper presents a novel framework, namely Deep Cross-modality Spectral Hashing (DCSH), to tackle the unsupervised learning problem of binary hash codes for efficient cross-moda…
MirrorNet: Bio-Inspired Camouflaged Object Segmentation
Jinnan Yan, Trung-Nghia Le, Khanh-Duy Nguyen +3
Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this paper, we propose a novel bio-inspired network, named the Mir…
A Convolutional Transformation Network for Malware Classification
Duc-Ly Vu, Trong-Kha Nguyen, Tam V. Nguyen +3
Modern malware evolves various detection avoidance techniques to bypass the state-of-the-art detection methods. An emerging trend to deal with this issue is the combination of imag…
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…
Smart Mirror: Intelligent Makeup Recommendation and Synthesis
Tam V. Nguyen, Luoqi Liu
The female facial image beautification usually requires professional editing softwares, which are relatively difficult for common users. In this demo, we introduce a practical syst…
Novel Evaluation Metrics for Seam Carving based Image Retargeting
Tam V. Nguyen, Guangyu Gao
Image retargeting effectively resizes images by preserving the recognizability of important image regions. Most of retargeting methods rely on good importance maps as a cue to reta…
Salient Object Detection with Semantic Priors
Tam V. Nguyen, Luoqi Liu
Salient object detection has increasingly become a popular topic in cognitive and computational sciences, including computer vision and artificial intelligence research. In this pa…
GECKA3D: A 3D Game Engine for Commonsense Knowledge Acquisition
Erik Cambria, Tam V. Nguyen, Brian Cheng +2
Commonsense knowledge representation and reasoning is key for tasks such as artificial intelligence and natural language understanding. Since commonsense consists of information th…
Sense Beyond Expressions: Cuteness
Kang Wang, Tam V. Nguyen, Jiashi Feng +1
With the development of Internet culture, cuteness has become a popular concept. Many people are curious about what factors making a person look cute. However, there is rare resear…
Salient Object Detection via Augmented Hypotheses
Tam V. Nguyen, Jose Sepulveda
In this paper, we propose using \textit{augmented hypotheses} which consider objectness, foreground and compactness for salient object detection. Our algorithm consists of four bas…
Adaptive Nonparametric Image Parsing
Tam V. Nguyen, Canyi Lu, Jose Sepulveda +1
In this paper, we present an adaptive nonparametric solution to the image parsing task, namely annotating each image pixel with its corresponding category label. For a given test i…
Development of a Context Aware Virtual Smart Home Simulator
Tam Van Nguyen, Huy Nguyen, Deokjai Choi
Context awareness is the most important research area in ubiquitous computing. In particular, for smart home, context awareness attempts to bring the best services to the home habi…