3 citations · 3 across the 7 of their papers we have counts for
9 papers
NeuDonatello: Uncertainty-Aware Framework for Accurate Neural SDF Learning
Alvin Jinsung Choi, Wanhee Kim, Taeyun Kim +3
Neural surface reconstruction has emerged as a powerful paradigm for recovering high-quality 3D surfaces from multi-view images. However, recovering accurate geometry solely from R…
VIRD: View-Invariant Representation through Dual-Axis Transformation for Cross-View Pose Estimation
Juhye Park, Wooju Lee, Dasol Hong +4
Accurate global localization is critical for autonomous driving and robotics, but GNSS-based approaches often degrade due to occlusion and multipath effects. As an emerging alterna…
CoCoA-Mix: Confusion-and-Confidence-Aware Mixture Model for Context Optimization
Dasol Hong, Wooju Lee, Hyun Myung
Prompt tuning, which adapts vision-language models by freezing model parameters and optimizing only the prompt, has proven effective for task-specific adaptations. The core challen…
PIDLoc: Cross-View Pose Optimization Network Inspired by PID Controllers
Wooju Lee, Juhye Park, Dasol Hong +4
Accurate localization is essential for autonomous driving, but GNSS-based methods struggle in challenging environments such as urban canyons. Cross-view pose optimization offers an…
Contextrast: Contextual Contrastive Learning for Semantic Segmentation
Changki Sung, Wanhee Kim, Jungho An +3
Despite great improvements in semantic segmentation, challenges persist because of the lack of local/global contexts and the relationship between them. In this paper, we propose Co…
Domain Generalization with Vital Phase Augmentation
Ingyun Lee, Wooju Lee, Hyun Myung
Deep neural networks have shown remarkable performance in image classification. However, their performance significantly deteriorates with corrupted input data. Domain generalizati…
Object-Aware Domain Generalization for Object Detection
Wooju Lee, Dasol Hong, Hyungtae Lim +1
Single-domain generalization (S-DG) aims to generalize a model to unseen environments with a single-source domain. However, most S-DG approaches have been conducted in the field of…
X-MAS: Extremely Large-Scale Multi-Modal Sensor Dataset for Outdoor Surveillance in Real Environments
DongKi Noh, Changki Sung, Teayoung Uhm +12
In robotics and computer vision communities, extensive studies have been widely conducted regarding surveillance tasks, including human detection, tracking, and motion recognition…
Adversarial Attack for Asynchronous Event-based Data
Wooju Lee, Hyun Myung
Deep neural networks (DNNs) are vulnerable to adversarial examples that are carefully designed to cause the deep learning model to make mistakes. Adversarial examples of 2D images…