1 citations · 2 across the 10 of their papers we have counts for
6 papers · 1 filter
MR-Occ: Efficient Camera-LiDAR 3D Semantic Occupancy Prediction Using Hierarchical Multi-Resolution Voxel Representation
Minjae Seong, Jisong Kim, Geonho Bang +2
Accurate 3D perception is essential for understanding the environment in autonomous driving. Recent advancements in 3D semantic occupancy prediction have leveraged camera-LiDAR fus…
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object Detection
Jisong Kim, Minjae Seong, Jun Won Choi
Accurate and robust 3D object detection is a critical component in autonomous vehicles and robotics. While recent radar-camera fusion methods have made significant progress by fusi…
JoVALE: Detecting Human Actions in Video Using Audiovisual and Language Contexts
Taein Son, Soo Won Seo, Jisong Kim +2
Video Action Detection (VAD) entails localizing and categorizing action instances within videos, which inherently consist of diverse information sources such as audio, visual cues,…
JARViS: Detecting Actions in Video Using Unified Actor-Scene Context Relation Modeling
Seok Hwan Lee, Taein Son, Soo Won Seo +2
Video action detection (VAD) is a formidable vision task that involves the localization and classification of actions within the spatial and temporal dimensions of a video clip. Am…
PillarGen: Enhancing Radar Point Cloud Density and Quality via Pillar-based Point Generation Network
Jisong Kim, Geonho Bang, Kwangjin Choi +4
In this paper, we present a novel point generation model, referred to as Pillar-based Point Generation Network (PillarGen), which facilitates the transformation of point clouds fro…
RadarDistill: Boosting Radar-based Object Detection Performance via Knowledge Distillation from LiDAR Features
Geonho Bang, Kwangjin Choi, Jisong Kim +2
The inherent noisy and sparse characteristics of radar data pose challenges in finding effective representations for 3D object detection. In this paper, we propose RadarDistill, a…