20 citations · 29 across the 6 of their papers we have counts for
6 papers
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…
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…
FaR: Enhancing Multi-Concept Text-to-Image Diffusion via Concept Fusion and Localized Refinement
Gia-Nghia Tran, Quang-Huy Che, Trong-Tai Dam Vu +4
Generating multiple new concepts remains a challenging problem in the text-to-image task. Current methods often overfit when trained on a small number of samples and struggle with…
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…
Enhancing person re-identification via Uncertainty Feature Fusion Method and Auto-weighted Measure Combination
Quang-Huy Che, Le-Chuong Nguyen, Duc-Tuan Luu +1
Person re-identification (Re-ID) is a challenging task that involves identifying the same person across different camera views in surveillance systems. Current methods usually rely…
TwinLiteNet+: An Enhanced Multi-Task Segmentation Model for Autonomous Driving
Quang-Huy Che, Duc-Tri Le, Minh-Quan Pham +2
Semantic segmentation is a fundamental perception task in autonomous driving, particularly for identifying drivable areas and lane markings to enable safe navigation. However, most…