261 citations · 356 across the 34 of their papers we have counts for
11 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…
MambaGlue: Fast and Robust Local Feature Matching With Mamba
Kihwan Ryoo, Hyungtae Lim, Hyun Myung
In recent years, robust matching methods using deep learning-based approaches have been actively studied and improved in computer vision tasks. However, there remains a persistent…
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…
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…
eCDT: Event Clustering for Simultaneous Feature Detection and Tracking-
Sumin Hu, Yeeun Kim, Hyungtae Lim +2
Contrary to other standard cameras, event cameras interpret the world in an entirely different manner; as a collection of asynchronous events. Despite event camera's unique data ou…
A Single Correspondence Is Enough: Robust Global Registration to Avoid Degeneracy in Urban Environments
Hyungtae Lim, Suyong Yeon, Soohyun Ryu +6
Global registration using 3D point clouds is a crucial technology for mobile platforms to achieve localization or manage loop-closing situations. In recent years, numerous research…
Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional Network
Sungwon Hwang, Hyungtae Lim, Hyun Myung
Training a Convolutional Neural Network (CNN) to be robust against rotation has mostly been done with data augmentation. In this paper, another progressive vision of research direc…
ERASOR: Egocentric Ratio of Pseudo Occupancy-based Dynamic Object Removal for Static 3D Point Cloud Map Building
Hyungtae Lim, Sungwon Hwang, Hyun Myung
Scan data of urban environments often include representations of dynamic objects, such as vehicles, pedestrians, and so forth. However, when it comes to constructing a 3D point clo…
MSDPN: Monocular Depth Prediction with Partial Laser Observation using Multi-stage Neural Networks
Hyungtae Lim, Hyeonjae Gil, Hyun Myung
In this study, a deep-learning-based multi-stage network architecture called Multi-Stage Depth Prediction Network (MSDPN) is proposed to predict a dense depth map using a 2D LiDAR…