16 citations · 36 across the 8 of their papers we have counts for
9 papers
SADL: What to Ignore? A Benchmark for Subject-Aware Distractor Localization
Cao-Tri Nguyen, Nguyen-Khoa Luong, Vinh-Tiep Nguyen +1
Photographs frequently contain \emph{visual distractors} besides foregrounds and backgrounds of the intended subject, competing for attention and weakening composition. While moder…
EPEdit: Redefining Image Editing with Generative AI and User-Centric Design
Hoang-Phuc Nguyen, Dinh-Khoi Vo, Trong-Le Do +7
The demand for image manipulation has seen a significant increase recently. Traditional tools like Photoshop and Capture One, while powerful, require considerable expertise to use…
Forged Calamity: Benchmark for Cross-Domain Synthetic Disaster Detection in the Age of Diffusion
Duc-Manh Phan, Quoc-Duy Tran, Duy-Khang Do +9
The rapid advancement of text-to-image diffusion models has enabled the creation of highly photorealistic synthetic images that closely resemble real photographs, making it increas…
SHREC 2025: Retrieval of Optimal Objects for Multi-modal Enhanced Language and Spatial Assistance (ROOMELSA)
Trong-Thuan Nguyen, Viet-Tham Huynh, Quang-Thuc Nguyen +30
Recent 3D retrieval systems are typically designed for simple, controlled scenarios, such as identifying an object from a cropped image or a brief description. However, real-world…
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…
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…
TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval
Trung-Nghia Le, Tam V. Nguyen, Minh-Quan Le +30
3D object retrieval is an important yet challenging task that has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issu…
SketchANIMAR: Sketch-based 3D Animal Fine-Grained Retrieval
Trung-Nghia Le, Tam V. Nguyen, Minh-Quan Le +31
The retrieval of 3D objects has gained significant importance in recent years due to its broad range of applications in computer vision, computer graphics, virtual reality, and aug…