4 citations · 6 across the 8 of their papers we have counts for
9 papers
RECAST: Recasting Vision-Language Semantics into an Actionable Cost Map for Robot Navigation
Incheol Cho, Jintae Park, Jinkyu Kim +3
Safe and robust robot navigation across diverse environments requires a high-level understanding of complex scenes and the ability to carry it into stable motion. Recent works tack…
Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling
Seokha Moon, Minseung Lee, Joon Seo +2
End-to-end autonomous driving, which bypasses traditional modular pipelines by directly predicting future trajectories from sensor inputs, has recently achieved substantial progres…
ALIGN: Advanced Query Initialization with LiDAR-Image Guidance for Occlusion-Robust 3D Object Detection
Janghyun Baek, Mincheol Chang, Seokha Moon +2
Recent query-based 3D object detection methods using camera and LiDAR inputs have shown strong performance, but existing query initialization strategies,such as random sampling or…
SUPER-AD: Semantic Uncertainty-aware Planning for End-to-End Robust Autonomous Driving
Wonjeong Ryu, Seungjun Yu, Seokha Moon +4
End-to-End (E2E) planning has become a powerful paradigm for autonomous driving, yet current systems remain fundamentally uncertainty-blind. They assume perception outputs are full…
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…
Image-Guided Semantic Pseudo-LiDAR Point Generation for 3D Object Detection
Minseung Lee, Seokha Moon, Seung Joon Lee +2
In autonomous driving scenarios, accurate perception is becoming an even more critical task for safe navigation. While LiDAR provides precise spatial data, its inherent sparsity ma…
VisionTrap: Vision-Augmented Trajectory Prediction Guided by Textual Descriptions
Seokha Moon, Hyun Woo, Hongbeen Park +6
Predicting future trajectories for other road agents is an essential task for autonomous vehicles. Established trajectory prediction methods primarily use agent tracks generated by…
Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection
Seokha Moon, Hongbeen Park, Jungphil Kwon +2
In autonomous driving and robotics, there is a growing interest in utilizing short-term historical data to enhance multi-camera 3D object detection, leveraging the continuous and c…
ORA3D: Overlap Region Aware Multi-view 3D Object Detection
Wonseok Roh, Gyusam Chang, Seokha Moon +5
Current multi-view 3D object detection methods often fail to detect objects in the overlap region properly, and the networks' understanding of the scene is often limited to that of…