9 citations · 16 across the 20 of their papers we have counts for
20 papers
Are Visual Place Recognition Models Recognizing Places or Conditions? Distractor-Augmented Evaluation and Condition Suppression
Beomsu Kim, Minwoo Jung, Giseop Kim
Long-term Visual Place Recognition (VPR) is typically evaluated by matching queries from one condition against a database from another. Crowdsourced map databases, however, may mix…
Geometrically-Constrained Radar-Inertial Odometry via Continuous Point-Pose Uncertainty Modeling
Wooseong Yang, Dongjae Lee, Minwoo Jung +1
Radar odometry is crucial for robust localization in challenging environments; however, the sparsity of reliable returns and distinctive noise characteristics impede its performanc…
TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory
Minwoo Jung, Dongjae Lee, Nived Chebrolu +3
Reliable localization is essential for sustainable forest management, as it allows robots to revisit and monitor the status of individual trees over long periods. In modern forestr…
TreeLoc: 6-DoF LiDAR Global Localization in Forests via Inter-Tree Geometric Matching
Minwoo Jung, Nived Chebrolu, Lucas Carvalho de Lima +3
Reliable localization is crucial for navigation in forests, where GPS is often degraded and LiDAR measurements are repetitive, occluded, and structurally complex. These conditions…
SHeRLoc: Synchronized Heterogeneous Radar Place Recognition for Cross-Modal Localization
Hanjun Kim, Minwoo Jung, Wooseong Yang +1
Despite the growing adoption of radar in robotics, the majority of research has been confined to homogeneous sensor types, overlooking the integration and cross-modality challenges…
The City that Never Settles: Simulation-based LiDAR Dataset for Long-Term Place Recognition Under Extreme Structural Changes
Hyunho Song, Dongjae Lee, Seunghun Oh +2
Large-scale construction and demolition significantly challenge long-term place recognition (PR) by drastically reshaping urban and suburban environments. Existing datasets predomi…
ImLPR: Image-based LiDAR Place Recognition using Vision Foundation Models
Minwoo Jung, Lanke Frank Tarimo Fu, Maurice Fallon +1
LiDAR Place Recognition (LPR) is a key component in robotic localization, enabling robots to align current scans with prior maps of their environment. While Visual Place Recognitio…
GaRLIO: Gravity enhanced Radar-LiDAR-Inertial Odometry
Chiyun Noh, Wooseong Yang, Minwoo Jung +2
Recently, gravity has been highlighted as a crucial constraint for state estimation to alleviate potential vertical drift. Existing online gravity estimation methods rely on pose e…
HeRCULES: Heterogeneous Radar Dataset in Complex Urban Environment for Multi-session Radar SLAM
Hanjun Kim, Minwoo Jung, Chiyun Noh +5
Recently, radars have been widely featured in robotics for their robustness in challenging weather conditions. Two commonly used radar types are spinning radars and phased-array ra…
HeLiOS: Heterogeneous LiDAR Place Recognition via Overlap-based Learning and Local Spherical Transformer
Minwoo Jung, Sangwoo Jung, Hyeonjae Gil +1
LiDAR place recognition is a crucial module in localization that matches the current location with previously observed environments. Most existing approaches in LiDAR place recogni…
MOANA: Multi-Radar Dataset for Maritime Odometry and Autonomous Navigation Application
Hyesu Jang, Wooseong Yang, Hanguen Kim +12
Maritime environmental sensing requires overcoming challenges from complex conditions such as harsh weather, platform perturbations, large dynamic objects, and the requirement for…
Quantitative 3D Map Accuracy Evaluation Hardware and Algorithm for LiDAR(-Inertial) SLAM
Sanghyun Hahn, Seunghun Oh, Minwoo Jung +2
Accuracy evaluation of a 3D pointcloud map is crucial for the development of autonomous driving systems. In this work, we propose a user-independent software/hardware system that c…
ConPR: Ongoing Construction Site Dataset for Place Recognition
Dongjae Lee, Minwoo Jung, Ayoung Kim
Place recognition, an essential challenge in computer vision and robotics, involves identifying previously visited locations. Despite algorithmic progress, challenges related to ap…
Toward Robust LiDAR based 3D Object Detection via Density-Aware Adaptive Thresholding
Eunho Lee, Minwoo Jung, Ayoung Kim
Robust 3D object detection is a core challenge for autonomous mobile systems in field robotics. To tackle this issue, many researchers have demonstrated improvements in 3D object d…
Imaging radar and LiDAR image translation for 3-DOF extrinsic calibration
Sangwoo Jung, Hyesu Jang, Minwoo Jung +2
The integration of sensor data is crucial in the field of robotics to take full advantage of the various sensors employed. One critical aspect of this integration is determining th…
LodeStar: Maritime Radar Descriptor for Semi-Direct Radar Odometry
Hyesu Jang, Minwoo Jung, Myung-Hwan Jeon +1
Maritime radars are prevalently adopted to capture the vessel's omnidirectional data as imagery. Nevertheless, inherent challenges persist with marine radars, including limited fre…
LiDAR Odometry Survey: Recent Advancements and Remaining Challenges
Dongjae Lee, Minwoo Jung, Wooseong Yang +1
Odometry is crucial for robot navigation, particularly in situations where global positioning methods like global positioning system (GPS) are unavailable. The main goal of odometr…
HeLiPR: Heterogeneous LiDAR Dataset for inter-LiDAR Place Recognition under Spatiotemporal Variations
Minwoo Jung, Wooseong Yang, Dongjae Lee +3
Place recognition is crucial for robot localization and loop closure in simultaneous localization and mapping (SLAM). Light Detection and Ranging (LiDAR), known for its robust sens…
RaPlace: Place Recognition for Imaging Radar using Radon Transform and Mutable Threshold
Hyesu Jang, Minwoo Jung, Ayoung Kim
Due to the robustness in sensing, radar has been highlighted, overcoming harsh weather conditions such as fog and heavy snow. In this paper, we present a novel radar-only place rec…
TRansPose: Large-Scale Multispectral Dataset for Transparent Object
Jeongyun Kim, Myung-Hwan Jeon, Sangwoo Jung +4
Transparent objects are encountered frequently in our daily lives, yet recognizing them poses challenges for conventional vision sensors due to their unique material properties, no…