33 citations · 33 across the 13 of their papers we have counts for
14 papers
MatcherCompass: A Deployment-Aware Benchmark to Guide Image Matcher Selection in the Wild
Hyunwoo Kim, Giseop Kim
Field robots operating across time of day and sensing modalities require accurate image correspondences within onboard time and resource budgets. However, accuracy and runtime repo…
NaViRrator: Robot Navigation from Human-Readable Maps through a Learned Visual Route
Ayun Lee, Jiseon Kim, Giseop Kim
Human-readable maps provide an intuitive interface for specifying robot destinations, but connecting their schematic geometry to egocentric observations remains challenging. We pre…
LT-Mem: Volatility-Aware Spatio-Temporal Memory for Lifelong Scene Understanding
Yumin Lee, Hyoseok Ju, Giseop Kim
Long-term robot operation in evolving environments requires object-level understanding that persists across repeated revisits. Existing systems either overwrite history to maintain…
Mag4D-SLAM Dataset: A Repeated-Traversal Multi-Modal 4D Geomagnetic Dataset for Localization and Mapping
Bibhutibhusan Nayak, Hyoseok Ju, Giseop Kim
Geomagnetic sensing offers an infrastructure-free, absolute orientation reference that is robust to GNSS denial and visual degradation, yet no large-scale outdoor robotics dataset…
Self-supervised Geometry Reasoning for LiDAR Simultaneous Localization and Mapping
Jiwoo Kim, Jinwoo Lee, Woojae Shin +2
LiDAR simultaneous localization and mapping (SLAM) relies on local geometric quantities such as covariances, correspondences, and surface structures. However, most existing pipelin…
Learning Point Cloud Geometry as a Statistical Manifold: Theory and Practice
Jinwoo Lee, Jiwoo Kim, Woojae Shin +2
Point clouds are a fundamental representation for robotic perception tasks such as localization, mapping, and object pose estimation. However, LiDAR-acquired point clouds are inher…
MR.ScaleMaster: Scale-Consistent Collaborative Mapping from Crowd-Sourced Monocular Videos
Hyoseok Ju, Giseop Kim
Crowd-sourced cooperative mapping combines monocular sessions from different front-ends, each an independently reconstructed keyframe sequence. Each session has its own local coord…
Have We Mastered Scale in Deep Monocular Visual SLAM? The ScaleMaster Dataset and Benchmark
Hyoseok Ju, Bokeon Suh, Giseop Kim
Recent advances in deep monocular visual Simultaneous Localization and Mapping (SLAM) have achieved impressive accuracy and dense reconstruction capabilities, yet their robustness…
LAMP: Implicit Language Map for Robot Navigation
Sibaek Lee, Hyeonwoo Yu, Giseop Kim +1
Recent advances in vision-language models have made zero-shot navigation feasible, enabling robots to follow natural language instructions without requiring labeling. However, exis…
Inlier-Centric Post-Training Quantization for Object Detection Models
Minsu Kim, Dongyeun Lee, Jaemyung Yu +3
Object detection is pivotal in computer vision, yet its immense computational demands make deployment slow and power-hungry, motivating quantization. However, task-irrelevant morph…
Streaming Dense Voxel Representations for 3D Occupancy Prediction
Seokha Moon, Janghyun Baek, Yujin Jeong +5
In this paper, we explore dense voxel streaming for accurate and efficient 3D occupancy prediction. While dense voxel representations offer fine-grained spatial details and streami…
Narrowing your FOV with SOLiD: Spatially Organized and Lightweight Global Descriptor for FOV-constrained LiDAR Place Recognition
Hogyun Kim, Jiwon Choi, Taehu Sim +2
We often encounter limited FOV situations due to various factors such as sensor fusion or sensor mount in real-world robot navigation. However, the limited FOV interrupts the gener…
Addressing Diverging Training Costs using BEVRestore for High-resolution Bird's Eye View Map Construction
Minsu Kim, Giseop Kim, Sunwook Choi
Recent advancements in Bird's Eye View (BEV) fusion for map construction have demonstrated remarkable mapping of urban environments. However, their deep and bulky architecture incu…
BroadBEV: Collaborative LiDAR-camera Fusion for Broad-sighted Bird's Eye View Map Construction
Minsu Kim, Giseop Kim, Kyong Hwan Jin +1
A recent sensor fusion in a Bird's Eye View (BEV) space has shown its utility in various tasks such as 3D detection, map segmentation, etc. However, the approach struggles with ina…