2 citations · 2 across the 1 of their papers we have counts for
15 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…
DreamWaQ++: Obstacle-Aware Quadrupedal Locomotion With Resilient Multi-Modal Reinforcement Learning
I Made Aswin Nahrendra, Byeongho Yu, Minho Oh +5
Quadrupedal robots hold promising potential for applications in navigating cluttered environments with resilience akin to their animal counterparts. However, their floating base co…
Multi-Mapcher: Loop Closure Detection-Free Heterogeneous LiDAR Multi-Session SLAM Leveraging Outlier-Robust Registration for Autonomous Vehicles
Hyungtae Lim, Daebeom Kim, Hyun Myung
As various 3D light detection and ranging (LiDAR) sensors have been introduced to the market, research on multi-session simultaneous localization and mapping (MSS) using heterogene…
LVI-Q: Robust LiDAR-Visual-Inertial-Kinematic Odometry for Quadruped Robots Using Tightly-Coupled and Efficient Alternating Optimization
Kevin Christiansen Marsim, Minho Oh, Byeongho Yu +4
Autonomous navigation for legged robots in complex and dynamic environments relies on robust simultaneous localization and mapping (SLAM) systems to accurately map surroundings and…
SaWa-ML: Structure-Aware Pose Correction and Weight Adaptation-Based Robust Multi-Robot Localization
Junho Choi, Kihwan Ryoo, Jeewon Kim +6
Multi-robot localization is a crucial task for implementing multi-robot systems. Numerous researchers have proposed optimization-based multi-robot localization methods that use cam…
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…