3 citations · 3 across the 4 of their papers we have counts for
6 papers
Contextrast++: Robust Multi-Scale Contextual Contrastive Learning for Semantic Segmentation
Changki Sung, Hyungtae Lim, Wanhee Kim +2
Semantic segmentation has rapidly advanced with deep learning; however, challenges remain in effectively capturing local and global contexts as well as addressing the long-tailed d…
LQ-rPPG: A Label-Quantized Coarse-to-Fine Learning Framework for Remote Physiological Measurement
Jun Seong Lee, Samyeul Noh, Changki Sung +1
Remote photoplethysmography (rPPG) enables non-contact measurement of physiological signals from facial videos, offering strong potential for remote healthcare and daily health mon…
E2EGS: Event-to-Edge Gaussian Splatting for Pose-Free 3D Reconstruction
Yunsoo Kim, Changki Sung, Dasol Hong +1
The emergence of neural radiance fields (NeRF) and 3D Gaussian splatting (3DGS) has advanced novel view synthesis (NVS). These methods, however, require high-quality RGB inputs and…
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…
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…