2 citations · 4 across the 8 of their papers we have counts for
10 papers
DeSPITE: Exploring Contrastive Deep Skeleton-Pointcloud-IMU-Text Embeddings for Advanced Point Cloud Human Activity Understanding
Thomas Kreutz, Max Mühlhäuser, Alejandro Sanchez Guinea
Despite LiDAR (Light Detection and Ranging) being an effective privacy-preserving alternative to RGB cameras to perceive human activities, it remains largely underexplored in the c…
SafePath: Conformal Prediction for Safe LLM-Based Autonomous Navigation
Achref Doula, Max Mühlhäuser, Alejandro Sanchez Guinea
Large Language Models (LLMs) show growing promise in autonomous driving by reasoning over complex traffic scenarios to generate path plans. However, their tendencies toward overcon…
Whenever, Wherever: Towards Orchestrating Crowd Simulations with Spatio-Temporal Spawn Dynamics
Thomas Kreutz, Max Mühlhäuser, Alejandro Sanchez Guinea
Realistic crowd simulations are essential for immersive virtual environments, relying on both individual behaviors (microscopic dynamics) and overall crowd patterns (macroscopic ch…
LiOn-XA: Unsupervised Domain Adaptation via LiDAR-Only Cross-Modal Adversarial Training
Thomas Kreutz, Jens Lemke, Max Mühlhäuser +1
In this paper, we propose LiOn-XA, an unsupervised domain adaptation (UDA) approach that combines LiDAR-Only Cross-Modal (X) learning with Adversarial training for 3D LiDAR point c…
Unsupervised Driving Event Discovery Based on Vehicle CAN-data
Thomas Kreutz, Ousama Esbel, Max Mühlhäuser +1
The data collected from a vehicle's Controller Area Network (CAN) can quickly exceed human analysis or annotation capabilities when considering fleets of vehicles, which stresses t…
Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time Series
Thomas Kreutz, Max Mühlhäuser, Alejandro Sanchez Guinea
In this work, we address the problem of unsupervised moving object segmentation (MOS) in 4D LiDAR data recorded from a stationary sensor, where no ground truth annotations are invo…
Enhancing Privacy via Hierarchical Federated Learning
Aidmar Wainakh, Alejandro Sanchez Guinea, Tim Grube +1
Federated learning suffers from several privacy-related issues that expose the participants to various threats. A number of these issues are aggravated by the centralized architect…
Understanding SAT is in P
Alejandro Sanchez Guinea
We introduce the idea of an understanding with respect to a set of clauses as a satisfying truth assignment explained by the contexts of the literals in the clauses. Following this…
On computable abstractions (a conceptual introduction)
Alejandro Sanchez Guinea
This paper introduces abstractions that are meaningful for computers and that can be built and used according to computers' own criteria, i.e., computable abstractions. It is analy…
A Design Methodology for Software Measurement Programs
Alejandro Sanchez Guinea
Software measurement programs have emerged as compounds of several measurement activities that are pursued as part of a combined effort of several parties within a software organiz…