1 citations · 1 across the 8 of their papers we have counts for
8 papers
Efficient Motion Prediction: A Lightweight & Accurate Trajectory Prediction Model With Fast Training and Inference Speed
Alexander Prutsch, Horst Bischof, Horst Possegger
For efficient and safe autonomous driving, it is essential that autonomous vehicles can predict the motion of other traffic agents. While highly accurate, current motion prediction…
Vision-Language Guidance for LiDAR-based Unsupervised 3D Object Detection
Christian Fruhwirth-Reisinger, Wei Lin, Dušan Malić +2
Accurate 3D object detection in LiDAR point clouds is crucial for autonomous driving systems. To achieve state-of-the-art performance, the supervised training of detectors requires…
Into the Fog: Evaluating Robustness of Multiple Object Tracking
Nadezda Kirillova, M. Jehanzeb Mirza, Horst Bischof +1
State-of-the-art Multiple Object Tracking (MOT) approaches have shown remarkable performance when trained and evaluated on current benchmarks. However, these benchmarks primarily c…
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection
Jakub Micorek, Horst Possegger, Dominik Narnhofer +2
We propose a novel approach to video anomaly detection: we treat feature vectors extracted from videos as realizations of a random variable with a fixed distribution and model this…
Identifying and Extracting Pedestrian Behavior in Critical Traffic Situations
Martin Schachner, Bernd Schneider, Fabian Weissenbacher +4
A better understanding of interactive pedestrian behavior in critical traffic situations is essential for the development of enhanced pedestrian safety systems. Real-world traffic…
Robust Localization of Key Fob Using Channel Impulse Response of Ultra Wide Band Sensors for Keyless Entry Systems
Abhiram Kolli, Filippo Casamassima, Horst Possegger +1
Using neural networks for localization of key fob within and surrounding a car as a security feature for keyless entry is fast emerging. In this paper we study: 1) the performance…
GACE: Geometry Aware Confidence Enhancement for Black-Box 3D Object Detectors on LiDAR-Data
David Schinagl, Georg Krispel, Christian Fruhwirth-Reisinger +2
Widely-used LiDAR-based 3D object detectors often neglect fundamental geometric information readily available from the object proposals in their confidence estimation. This is most…
TAP: Targeted Prompting for Task Adaptive Generation of Textual Training Instances for Visual Classification
M. Jehanzeb Mirza, Leonid Karlinsky, Wei Lin +3
Vision and Language Models (VLMs), such as CLIP, have enabled visual recognition of a potentially unlimited set of categories described by text prompts. However, for the best visua…