10 citations · 13 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
KISS-Matcher: Fast and Robust Point Cloud Registration Revisited
Hyungtae Lim, Daebeom Kim, Gunhee Shin +5
While global point cloud registration systems have advanced significantly in all aspects, many studies have focused on specific components, such as feature extraction, graph-theore…
HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors
Hyungtae Lim, Seoyeon Jang, Benedikt Mersch +3
Moving object segmentation (MOS) using a 3D light detection and ranging (LiDAR) sensor is crucial for scene understanding and identification of moving objects. Despite the availabi…
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…