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20222026
most citedORA3D: Overlap Region Aware Multi-view 3D Object Detection

4 citations · 6 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2022★ 4 cited

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…