3 citations · 5 across the 5 of their papers we have counts for
5 papers
SpaRC-AD: A Baseline for Radar-Camera Fusion in End-to-End Autonomous Driving
Philipp Wolters, Johannes Gilg, Torben Teepe +1
End-to-end autonomous driving systems promise stronger performance through unified optimization of perception, motion forecasting, and planning. However, vision-based approaches fa…
SpaRC: Sparse Radar-Camera Fusion for 3D Object Detection
Philipp Wolters, Johannes Gilg, Torben Teepe +3
In this work, we present SpaRC, a novel Sparse fusion transformer for 3D perception that integrates multi-view image semantics with Radar and Camera point features. The fusion of r…
Spatial-Temporal Multi-Cuts for Online Multiple-Camera Vehicle Tracking
Fabian Herzog, Johannes Gilg, Philipp Wolters +2
Accurate online multiple-camera vehicle tracking is essential for intelligent transportation systems, autonomous driving, and smart city applications. Like single-camera multiple-o…
Lifting Multi-View Detection and Tracking to the Bird's Eye View
Torben Teepe, Philipp Wolters, Johannes Gilg +2
Taking advantage of multi-view aggregation presents a promising solution to tackle challenges such as occlusion and missed detection in multi-object tracking and detection. Recent…
Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D Perception
Philipp Wolters, Johannes Gilg, Torben Teepe +4
Low-cost, vision-centric 3D perception systems for autonomous driving have made significant progress in recent years, narrowing the gap to expensive LiDAR-based methods. The primar…