753 citations · 808 across the 14 of their papers we have counts for
20 papers · 1 filter
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…