326 citations · 432 across the 13 of their papers we have counts for
15 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…
EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye View
Torben Teepe, Philipp Wolters, Johannes Gilg +2
Multi-view aggregation promises to overcome the occlusion and missed detection challenge in multi-object detection and tracking. Recent approaches in multi-view detection and 3D ob…
Do We Still Need Non-Maximum Suppression? Accurate Confidence Estimates and Implicit Duplication Modeling with IoU-Aware Calibration
Johannes Gilg, Torben Teepe, Fabian Herzog +2
Object detectors are at the heart of many semi- and fully autonomous decision systems and are poised to become even more indispensable. They are, however, still lacking in accessib…
Explainable Model-Agnostic Similarity and Confidence in Face Verification
Martin Knoche, Torben Teepe, Stefan Hörmann +1
Recently, face recognition systems have demonstrated remarkable performances and thus gained a vital role in our daily life. They already surpass human face verification accountabi…
Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities
Fabian Herzog, Junpeng Chen, Torben Teepe +3
Smart City applications such as intelligent traffic routing or accident prevention rely on computer vision methods for exact vehicle localization and tracking. Due to the scarcity…
Face Morphing: Fooling a Face Recognition System Is Simple!
Stefan Hörmann, Tianlin Kong, Torben Teepe +3
State-of-the-art face recognition (FR) approaches have shown remarkable results in predicting whether two faces belong to the same identity, yielding accuracies between 92% and 100…
Towards a Deeper Understanding of Skeleton-based Gait Recognition
Torben Teepe, Johannes Gilg, Fabian Herzog +2
Gait recognition is a promising biometric with unique properties for identifying individuals from a long distance by their walking patterns. In recent years, most gait recognition…
The Box Size Confidence Bias Harms Your Object Detector
Johannes Gilg, Torben Teepe, Fabian Herzog +1
Countless applications depend on accurate predictions with reliable confidence estimates from modern object detectors. It is well known, however, that neural networks including obj…
Attention-based Partial Face Recognition
Stefan Hörmann, Zeyuan Zhang, Martin Knoche +2
Photos of faces captured in unconstrained environments, such as large crowds, still constitute challenges for current face recognition approaches as often faces are occluded by obj…
Lightweight Multi-Branch Network for Person Re-Identification
Fabian Herzog, Xunbo Ji, Torben Teepe +3
Person Re-Identification aims to retrieve person identities from images captured by multiple cameras or the same cameras in different time instances and locations. Because of its i…
GaitGraph: Graph Convolutional Network for Skeleton-Based Gait Recognition
Torben Teepe, Ali Khan, Johannes Gilg +3
Gait recognition is a promising video-based biometric for identifying individual walking patterns from a long distance. At present, most gait recognition methods use silhouette ima…