9 papers
VIPS: Vehicle-Infrastructure Cooperative Planning Benchmark via Pseudo-Simulation
Hoonhee Cho, Jae-Young Kang, Giwon Lee +3
End-to-end autonomous driving in urban environments requires robust decision-making under partial observability and complex multi-agent interactions. Severe occlusions and dense tr…
GoStop: Reinforcement Learning for Adaptive Temporal Aggregation in Event-Based Feature Tracking
Youngho Kim, Hoonhee Cho, Jae-Young Kang +1
Feature tracking plays a fundamental role in understanding scene motion and supports various downstream tasks. Event cameras, with their high temporal resolution and asynchronous s…
HEAT: Heterogeneous End-to-End Autonomous Driving via Trajectory-Guided World Models
Hoonhee Cho, Giwon Lee, Jae-Young Kang +3
End-to-end autonomous driving has emerged as a compelling alternative to traditional modular pipelines by directly mapping raw sensor data to driving actions. While recent approach…
Event6D: Event-based Novel Object 6D Pose Tracking
Jae-Young Kang, Hoonhee Cho, Taeyeop Lee +4
Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion bl…
DSERT-RoLL: Robust Multi-Modal Perception for Diverse Driving Conditions with Stereo Event-RGB-Thermal Cameras, 4D Radar, and Dual-LiDAR
Hoonhee Cho, Jae-Young Kang, Yuhwan Jeong +4
In this paper, we present DSERT-RoLL, a driving dataset that incorporates stereo event, RGB, and thermal cameras together with 4D radar and dual LiDAR, collected across diverse wea…
VR-Drive: Viewpoint-Robust End-to-End Driving with Feed-Forward 3D Gaussian Splatting
Hoonhee Cho, Jae-Young Kang, Giwon Lee +4
End-to-end autonomous driving (E2E-AD) has emerged as a promising paradigm that unifies perception, prediction, and planning into a holistic, data-driven framework. However, achiev…
Unleashing the Temporal Potential of Stereo Event Cameras for Continuous-Time 3D Object Detection
Jae-Young Kang, Hoonhee Cho, Kuk-Jin Yoon
3D object detection is essential for autonomous systems, enabling precise localization and dimension estimation. While LiDAR and RGB cameras are widely used, their fixed frame rate…
Ev-3DOD: Pushing the Temporal Boundaries of 3D Object Detection with Event Cameras
Hoonhee Cho, Jae-young Kang, Youngho Kim +1
Detecting 3D objects in point clouds plays a crucial role in autonomous driving systems. Recently, advanced multi-modal methods incorporating camera information have achieved notab…
Temporal Event Stereo via Joint Learning with Stereoscopic Flow
Hoonhee Cho, Jae-Young Kang, Kuk-Jin Yoon
Event cameras are dynamic vision sensors inspired by the biological retina, characterized by their high dynamic range, high temporal resolution, and low power consumption. These fe…