1 citations · 1 across the 13 of their papers we have counts for
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Lang3DSeg: Annotation-Free Open-Vocabulary 3D Segmentation with Point Transformers
Cigdem Kokenoz, Amir Salarpour, Alkim Domeke +5
Accurate 3D semantic perception is critical for safe autonomous navigation. However, supervised LiDAR segmentation remains tied to closed taxonomies and to the cost of point-wise m…
GATE: Reliability-Gated Gaussian Evidence Fusion for Training-Free Test-Time Adaptation of Vision-Language Models
Pedram MohajerAnsari, Amir Salarpour, Run Wang +1
Vision-language models such as CLIP and SigLIP provide strong zero-shot recognition, but their predictions can degrade when deployed on target data that differ from the pretraining…
Distilling Vision-Language Models for Robust Traffic Sign Perception in Autonomous Vehicles
Pedram MohajerAnsari, Amir Salarpour, Mert D. Pesé
Traffic sign recognition (TSR) models based on deep neural networks achieve strong clean-data performance but remain vulnerable to physically realizable adversarial attacks, includ…
Adversarial Prompts for Acceptance Collapse in Speculative Decoding
Run Wang, Chaoyi Zhou, Xi Liu +7
Lossless acceleration schemes, such as speculative decoding, promise significant inference speedups by relying on dynamic token-level alignment between a draft and a target model.…
Budget-Aware Adaptive Adversarial Patches for Black-Box Object Detection
Pedram MohajerAnsari, Amir Salarpour, David Fernandez +1
Adversarial patches pose a practical threat to modern object detectors. Prior work shows vulnerability, but three gaps limit actionable insight: (i) few \emph{score-based black-box…
Understanding Adversarial Transferability in Vision-Language Models for Autonomous Driving: A Cross-Architecture Analysis
David Fernandez, Pedram MohajerAnsari, Amir Salarpour +1
Vision-language models (VLMs) are increasingly used in autonomous driving because they combine visual perception with language-based reasoning, supporting more interpretable decisi…
Comparative Analysis of Patch Attack on VLM-Based Autonomous Driving Architectures
David Fernandez, Pedram MohajerAnsari, Amir Salarpour +3
Vision-language models are emerging for autonomous driving, yet their robustness to physical adversarial attacks remains unexplored. This paper presents a systematic framework for…
SLNet: A Super-Lightweight Geometry-Adaptive Network for 3D Point Cloud Recognition
Mohammad Saeid, Amir Salarpour, Pedram MohajerAnsari +1
We present SLNet, a lightweight backbone for 3D point cloud recognition designed to achieve strong performance without the computational cost of many recent attention, graph, and d…
NPNet: A Non-Parametric Network with Adaptive Gaussian-Fourier Positional Encoding for 3D Classification and Segmentation
Mohammad Saeid, Amir Salarpour, Pedram MohajerAnsari +1
We present NPNet, a fully non-parametric approach for 3D point-cloud classification and part segmentation. NPNet contains no learned weights; instead, it builds point features usin…
FlexMap: Robust HD Map Construction under Flexible Camera Configurations
Run Wang, Chaoyi Zhou, Amir Salarpour +5
High-definition (HD) maps provide essential semantic information about road structures for autonomous driving, but existing HD map construction methods typically require calibrated…