1 citations · 1 across the 13 of their papers we have counts for
4 papers · 1 filter
David vs. Goliath: A comparative study of different-sized LLMs for code generation in the domain of automotive scenario generation
Philipp Bauerfeind, Amir Salarpour, David Fernandez +3
Scenario simulation is central to testing autonomous driving systems. Scenic, a domain-specific language (DSL) for CARLA, enables precise and reproducible scenarios, but NL-to-Scen…
Enhancing 3D Point Cloud Classification with ModelNet-R and Point-SkipNet
Mohammad Saeid, Amir Salarpour, Pedram MohajerAnsari
The classification of 3D point clouds is crucial for applications such as autonomous driving, robotics, and augmented reality. However, the commonly used ModelNet40 dataset suffers…
Toward Inherently Robust VLMs Against Visual Perception Attacks
Pedram MohajerAnsari, Amir Salarpour, Michael Kühr +6
Autonomous vehicles rely on deep neural networks (DNNs) for traffic sign recognition, lane centering, and vehicle detection, yet these models are vulnerable to attacks that induce…
Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding
Marzieh Mohammadi, Amir Salarpour, Pedram MohajerAnsari
We introduce Point-LN, a novel lightweight framework engineered for efficient 3D point cloud classification. Point-LN integrates essential non-parametric components-such as Farthes…