7.7k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Kiet Van Nguyen3 profiles21 · h 21
- N. Nguyen17 · h 22
- Son T. Luu2 profiles17 · h 10
- Nguyen Tri Toan Phuc2 profiles14 · h 4
- Quan M. Nguyen13 · h 9
- Trung-Nghia Le2 profiles12 · h 17
- Minh-Triet Tran3 profiles9 · h 11
- Tam V. Nguyen2 profiles9 · h 30
- A. Peleg8 · h 15
- Dieu D. Nguyen8 · h 13
- M. Tran2 profiles8 · h 24
- Phong Quoc Vo8 · h 2
- Ho Chi Minh City University of ScienceVN125 papers
- Ho Chi Minh City University of TechnologyVN29 papers
- Ho Chi Minh City International UniversityVN26 papers
- Ho Chi Minh City University of EducationVN14 papers
- Vietnam Academy of Science and TechnologyVN14 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- The University of TokyoJP10 papers
- Institute for Nuclear Science and TechnologyVN9 papers
- University of DaytonUS9 papers
- Vietnam National University, HanoiVN9 papers
- Tohoku UniversityJP8 papers
- Ton Duc Thang UniversityVN8 papers
44 papers · 1 filter
Computer Vision by YOLOs for Detection of Major Diseases in Vietnamese Custard Apple Using Fruit Imagery
Tri Nhut Do, Quoc Tuan Vo
Amid Vietnam rapid digital transformation in agriculture, the integration of artificial intelligence technologies for identifying, monitoring, and predicting crop pests and disease…
Vision And Text Transformer For Predicting Answerability On Visual Question Answering
Tung Le, Huy Tien Nguyen, Le Minh Nguyen
Answerability on Visual Question Answering is a novel and attractive task to predict answerable scores between images and questions in multi-modal data. Existing works often utiliz…
VietFashion: Benchmarking Sketch-Text Composed Image Retrieval for Cultural Outfits
Hoang-Nguyen Cao, Le-Hoang Bui, Dinh-Khoi Vo +2
Cultural garments pose a unique challenge for visual retrieval systems, as their identity often depends on subtle structural and symbolic details that are poorly captured by standa…
TwinMixing: A Shuffle-Aware Feature Interaction Model for Multi-Task Segmentation
Minh-Khoi Do, Huy Che, Dinh-Duy Phan +2
Accurate and efficient perception is essential for autonomous driving, where segmentation tasks such as drivable-area and lane segmentation provide critical cues for motion plannin…
R&D: Balancing Reliability and Diversity in Synthetic Data Augmentation for Semantic Segmentation
Huy Che, Dinh-Duy Phan, Duc-Khai Lam
Collecting and annotating datasets for pixel-level semantic segmentation tasks are highly labor-intensive. Data augmentation provides a viable solution by enhancing model generaliz…
Fusionista2.0: Efficiency Retrieval System for Large-Scale Datasets
Huy M. Le, Dat Tien Nguyen, Phuc Binh Nguyen +8
The Video Browser Showdown (VBS) challenges systems to deliver accurate results under strict time constraints. To meet this demand, we present Fusionista2.0, a streamlined video re…
Comparative Study of UNet-based Architectures for Liver Tumor Segmentation in Multi-Phase Contrast-Enhanced Computed Tomography
Doan-Van-Anh Ly, Thanh-Hai Le, Thi-Thu-Hien Pham
Segmentation of liver structures in multi-phase contrast-enhanced computed tomography (CECT) plays a crucial role in computer-aided diagnosis and treatment planning. In this study,…
SHREC 2025: Protein surface shape retrieval including electrostatic potential
Taher Yacoub, Camille Depenveiller, Atsushi Tatsuma +25
This SHREC 2025 track dedicated to protein surface shape retrieval involved 9 participating teams. We evaluated the performance in retrieval of 15 proposed methods on a large datas…
Online 3D Multi-Camera Perception through Robust 2D Tracking and Depth-based Late Aggregation
Vu-Minh Le, Thao-Anh Tran, Duc Huy Do +3
Multi-Target Multi-Camera Tracking (MTMC) is an essential computer vision task for automating large-scale surveillance. With camera calibration and depth information, the targets i…
A Re-ranking Method using K-nearest Weighted Fusion for Person Re-identification
Huy Che, Le-Chuong Nguyen, Gia-Nghia Tran +2
In person re-identification, re-ranking is a crucial step to enhance the overall accuracy by refining the initial ranking of retrieved results. Previous studies have mainly focused…
ReCap: Event-Aware Image Captioning with Article Retrieval and Semantic Gaussian Normalization
Thinh-Phuc Nguyen, Thanh-Hai Nguyen, Gia-Huy Dinh +3
Image captioning systems often produce generic descriptions that fail to capture event-level semantics which are crucial for applications like news reporting and digital archiving.…
Multi-Level CLS Token Fusion for Contrastive Learning in Endoscopy Image Classification
Y Hop Nguyen, Doan Anh Phan Huu, Trung Thai Tran +4
We present a unified vision-language framework tailored for ENT endoscopy image analysis that simultaneously tackles three clinically-relevant tasks: image classification, image-to…
EVENT-Retriever: Event-Aware Multimodal Image Retrieval for Realistic Captions
Dinh-Khoi Vo, Van-Loc Nguyen, Minh-Triet Tran +1
Event-based image retrieval from free-form captions presents a significant challenge: models must understand not only visual features but also latent event semantics, context, and…
Event-Enriched Image Analysis Grand Challenge at ACM Multimedia 2025
Thien-Phuc Tran, Minh-Quang Nguyen, Minh-Triet Tran +7
The Event-Enriched Image Analysis (EVENTA) Grand Challenge, hosted at ACM Multimedia 2025, introduces the first large-scale benchmark for event-level multimodal understanding. Trad…
Person Re-Identification System at Semantic Level based on Pedestrian Attributes Ontology
Ngoc Q. Ly, Hieu N. M. Cao, Thi T. Nguyen
Person Re-Identification (Re-ID) is a very important task in video surveillance systems such as tracking people, finding people in public places, or analysing customer behavior in…
FA-Seg: A Fast and Accurate Diffusion-Based Method for Open-Vocabulary Segmentation
Huy Che, Vinh-Tiep Nguyen
Open-vocabulary semantic segmentation (OVSS) aims to segment objects from arbitrary text categories without requiring densely annotated datasets. Although contrastive learning base…
OpenEvents V1: Large-Scale Benchmark Dataset for Multimodal Event Grounding
Hieu Nguyen, Phuc-Tan Nguyen, Thien-Phuc Tran +4
We introduce OpenEvents V1a large-scale benchmark dataset designed to advance event-centric vision-language understanding. Unlike conventional image captioning and retrieval datase…
Lifelong Whole Slide Image Analysis: Online Vision-Language Adaptation and Past-to-Present Gradient Distillation
Doanh C. Bui, Hoai Luan Pham, Vu Trung Duong Le +4
Whole Slide Images (WSIs) play a crucial role in accurate cancer diagnosis and prognosis, as they provide tissue details at the cellular level. However, the rapid growth of computa…
From Visual Explanations to Counterfactual Explanations with Latent Diffusion
Tung Luu, Nam Le, Duc Le +1
Visual counterfactual explanations are ideal hypothetical images that change the decision-making of the classifier with high confidence toward the desired class while remaining vis…
Triply Laplacian Scale Mixture Modeling for Seismic Data Noise Suppression
Sirui Pan, Zhiyuan Zha, Shigang Wang +6
Sparsity-based tensor recovery methods have shown great potential in suppressing seismic data noise. These methods exploit tensor sparsity measures capturing the low-dimensional st…
MEX: Memory-efficient Approach to Referring Multi-Object Tracking
Huu-Thien Tran, Phuoc-Sang Pham, Thai-Son Tran +1
Referring Multi-Object Tracking (RMOT) is a relatively new concept that has rapidly gained traction as a promising research direction at the intersection of computer vision and nat…
QMaxViT-Unet+: A Query-Based MaxViT-Unet with Edge Enhancement for Scribble-Supervised Segmentation of Medical Images
Thien B. Nguyen-Tat, Hoang-An Vo, Phuoc-Sang Dang
The deployment of advanced deep learning models for medical image segmentation is often constrained by the requirement for extensively annotated datasets. Weakly-supervised learnin…
Stratified Domain Adaptation: A Progressive Self-Training Approach for Scene Text Recognition
Kha Nhat Le, Hoang-Tuan Nguyen, Hung Tien Tran +1
Unsupervised domain adaptation (UDA) has become increasingly prevalent in scene text recognition (STR), especially where training and testing data reside in different domains. The…
Enhanced Generative Data Augmentation for Semantic Segmentation via Stronger Guidance
Quang-Huy Che, Duc-Tri Le, Bich-Nga Pham +2
Data augmentation is crucial for pixel-wise annotation tasks like semantic segmentation, where labeling requires significant effort and intensive labor. Traditional methods, involv…