activity
20162026
most citedShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics

51 citations · 164 across the 49 of their papers we have counts for

collaborators
Showing cs.CVShow all

46 papers · 1 filter

cs.CV2026

VisionQ: VLM-as-a-Judge Taxonomy, Dataset and Benchmark for Qualitative Analysis in Computer Vision

Vu Dinh Xuan, Duc-Hai Nguyen, Minh-Dung Dao +6

Qualitative comparison figures are central evidence in computer vision papers, and vision-language models (VLMs) are increasingly used to judge them. Yet existing benchmarks score…

cs.CV2026

Evaluating Mesh Reconstruction Methods for Crop Phenotyping

Karanvir Singh, Theo Morales, Binh-Son Hua +1

Phenotyping an agricultural crop is crucial for studying its entire life cycle, as it provides vital insights to improve yield and, ultimately, food production. Doing the same for…

cs.CV2026

TruncGradGS: Improved 3D Gaussian Splatting via Truncated Gradient Updates

Theo Morales, Nhat-Quynh Le-Pham, Robin Atkins +1

3D Gaussian Splatting has become a de facto scene representation for novel view synthesis, yet robustly learning 3D Gaussian primitives from visual input remains challenging. Stand…

cs.CV2026

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation

Long Vu, Tan Ngo, Animesh Karnewar +5

Modern image-and-text-to-video diffusion models can synthesize highly realistic videos by iteratively denoising an initial Gaussian noise tensor conditioned on reference image and…

cs.CV2026

SwiftTailor: Efficient 3D Garment Generation with Geometry Image Representation

Phuc Pham, Uy Dieu Tran, Binh-Son Hua +1

Realistic and efficient 3D garment generation remains a longstanding challenge in computer vision and digital fashion. Existing methods typically rely on large vision- language mod…

cs.CV2025

FROMAT: Multiview Material Appearance Transfer via Few-Shot Self-Attention Adaptation

Hubert Kompanowski, Varun Jampani, Aaryaman Vasishta +1

Multiview diffusion models have rapidly emerged as a powerful tool for content creation with spatial consistency across viewpoints, offering rich visual realism without requiring e…

cs.CV2025

Power of Boundary and Reflection: Semantic Transparent Object Segmentation using Pyramid Vision Transformer with Transparent Cues

Tuan-Anh Vu, Hai Nguyen-Truong, Ziqiang Zheng +4

Glass is a prevalent material among solid objects in everyday life, yet segmentation methods struggle to distinguish it from opaque materials due to its transparency and reflection…

cs.CV2025

Color Alignment in Diffusion

Ka Chun Shum, Binh-Son Hua, Duc Thanh Nguyen +1

Diffusion models have shown great promise in synthesizing visually appealing images. However, it remains challenging to condition the synthesis at a fine-grained level, for instanc…

cs.CV2025

Text-to-3D Generation using Jensen-Shannon Score Distillation

Khoi Do, Binh-Son Hua

Score distillation sampling is an effective technique to generate 3D models from text prompts, utilizing pre-trained large-scale text-to-image diffusion models as guidance. However…

cs.CV2024

LiftRefine: Progressively Refined View Synthesis from 3D Lifting with Volume-Triplane Representations

Tung Do, Thuan Hoang Nguyen, Anh Tuan Tran +2

We propose a new view synthesis method via synthesizing a 3D neural field from both single or few-view input images. To address the ill-posed nature of the image-to-3D generation p…

cs.CV2024

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation

Duc-Hai Pham, Tung Do, Phong Nguyen +3

We propose SharpDepth, a novel approach to monocular metric depth estimation that combines the metric accuracy of discriminative depth estimation methods (e.g., Metric3D, UniDepth)…

cs.CV2024

ModeDreamer: Mode Guiding Score Distillation for Text-to-3D Generation using Reference Image Prompts

Uy Dieu Tran, Minh Luu, Phong Ha Nguyen +2

Existing Score Distillation Sampling (SDS)-based methods have driven significant progress in text-to-3D generation. However, 3D models produced by SDS-based methods tend to exhibit…

cs.CV2024

Dream-in-Style: Text-to-3D Generation Using Stylized Score Distillation

Hubert Kompanowski, Binh-Son Hua

We present a method to generate 3D objects in styles. Our method takes a text prompt and a style reference image as input and reconstructs a neural radiance field to synthesize a 3…

cs.CV2024

Vision-Aware Text Features in Referring Image Segmentation: From Object Understanding to Context Understanding

Hai Nguyen-Truong, E-Ro Nguyen, Tuan-Anh Vu +3

Referring image segmentation is a challenging task that involves generating pixel-wise segmentation masks based on natural language descriptions. The complexity of this task increa…

cs.CV2024★ 1 cited

DiDA: Video Object Segmentation with Distillation Learning of Deformable Attention

Quang-Trung Truong, Duc Thanh Nguyen, Binh-Son Hua +1

Video object segmentation is a fundamental research problem in computer vision. Recent techniques have often applied attention mechanism to object representation learning from vide…

cs.CV2023

Catch Me If You Can Describe Me: Open-Vocabulary Camouflaged Instance Segmentation with Diffusion

Tuan-Anh Vu, Duc Thanh Nguyen, Qing Guo +4

Text-to-image diffusion techniques have shown exceptional capabilities in producing high-quality, dense visual predictions from open-vocabulary text. This indicates a strong correl…

cs.CV2023

DiverseDream: Diverse Text-to-3D Synthesis with Augmented Text Embedding

Uy Dieu Tran, Minh Luu, Phong Ha Nguyen +2

Text-to-3D synthesis has recently emerged as a new approach to sampling 3D models by adopting pretrained text-to-image models as guiding visual priors. An intriguing but underexplo…

cs.CV2023

Test-Time Augmentation for 3D Point Cloud Classification and Segmentation

Tuan-Anh Vu, Srinjay Sarkar, Zhiyuan Zhang +2

Data augmentation is a powerful technique to enhance the performance of a deep learning task but has received less attention in 3D deep learning. It is well known that when 3D shap…

cs.CV2023★ 1 cited

Advances in 3D Neural Stylization: A Survey

Yingshu Chen, Guocheng Shao, Ka Chun Shum +2

Modern artificial intelligence offers a novel and transformative approach to creating digital art across diverse styles and modalities like images, videos and 3D data, unleashing t…

cs.CV2023

Locally Stylized Neural Radiance Fields

Hong-Wing Pang, Binh-Son Hua, Sai-Kit Yeung

In recent years, there has been increasing interest in applying stylization on 3D scenes from a reference style image, in particular onto neural radiance fields (NeRF). While perfo…

cs.CV2023

Language-driven Object Fusion into Neural Radiance Fields with Pose-Conditioned Dataset Updates

Ka Chun Shum, Jaeyeon Kim, Binh-Son Hua +2

Neural radiance field is an emerging rendering method that generates high-quality multi-view consistent images from a neural scene representation and volume rendering. Although neu…

cs.CV2023

GaPro: Box-Supervised 3D Point Cloud Instance Segmentation Using Gaussian Processes as Pseudo Labelers

Tuan Duc Ngo, Binh-Son Hua, Khoi Nguyen

Instance segmentation on 3D point clouds (3DIS) is a longstanding challenge in computer vision, where state-of-the-art methods are mainly based on full supervision. As annotating g…

cs.CV2023

Conditional 360-degree Image Synthesis for Immersive Indoor Scene Decoration

Ka Chun Shum, Hong-Wing Pang, Binh-Son Hua +2

In this paper, we address the problem of conditional scene decoration for 360-degree images. Our method takes a 360-degree background photograph of an indoor scene and generates de…

cs.CV2023★ 4 cited

ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution

Tuan Duc Ngo, Binh-Son Hua, Khoi Nguyen

Existing 3D instance segmentation methods are predominated by the bottom-up design -- manually fine-tuned algorithm to group points into clusters followed by a refinement network.…