activity
20242026
collaborators

6 papers

cs.CV2026

SafeDrive: Fine-Grained Safety Reasoning for End-to-End Driving in a Sparse World

Jungho Kim, Jiyong Oh, Seunghoon Yu +3

The end-to-end (E2E) paradigm, which maps sensor inputs directly to driving decisions, has recently attracted significant attention due to its unified modeling capability and scala…

cs.RO2026

CarPLAN: Context-Adaptive and Robust Planning with Dynamic Scene Awareness for Autonomous Driving

Junyong Yun, Jungho Kim, ByungHyun Lee +5

Imitation learning (IL) is widely used for motion planning in autonomous driving due to its data efficiency and access to real-world driving data. For safe and robust real-world dr…

cs.RO2026

STONE Dataset: A Scalable Multi-Modal Surround-View 3D Traversability Dataset for Off-Road Robot Navigation

Konyul Park, Daehun Kim, Jiyong Oh +7

Reliable off-road navigation requires accurate estimation of traversable regions and robust perception under diverse terrain and sensing conditions. However, existing datasets lack…

cs.CV2025

OnlineBEV: Recurrent Temporal Fusion in Bird's Eye View Representations for Multi-Camera 3D Perception

Junho Koh, Youngwoo Lee, Jungho Kim +2

Multi-view camera-based 3D perception can be conducted using bird's eye view (BEV) features obtained through perspective view-to-BEV transformations. Several studies have shown tha…

cs.CV2025

ProtoOcc: Accurate, Efficient 3D Occupancy Prediction Using Dual Branch Encoder-Prototype Query Decoder

Jungho Kim, Changwon Kang, Dongyoung Lee +2

In this paper, we introduce ProtoOcc, a novel 3D occupancy prediction model designed to predict the occupancy states and semantic classes of 3D voxels through a deep semantic under…

cs.CV2024

Mask2Map: Vectorized HD Map Construction Using Bird's Eye View Segmentation Masks

Sehwan Choi, Jungho Kim, Hongjae Shin +1

In this paper, we introduce Mask2Map, a novel end-to-end online HD map construction method designed for autonomous driving applications. Our approach focuses on predicting the clas…