4 citations · 4 across the 10 of their papers we have counts for
9 papers · 1 filter
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…
Sat3R: Satellite DSM Reconstruction via RPC-Aware Depth Fine-tuning
Qiaoyi Yang, Chaoyi Zhou, Xi Liu +9
Accurate Digital Surface Model (DSM) reconstruction from satellite imagery is critical for applications such as disaster response, urban planning, and large-scale geographic mappin…
FF3R: Feedforward Feature 3D Reconstruction from Unconstrained views
Chaoyi Zhou, Run Wang, Feng Luo +4
Recent advances in vision foundation models have revolutionized geometry reconstruction and semantic understanding. Yet, most of the existing approaches treat these capabilities in…
DisPatch: Disarming Adversarial Patches in Object Detection with Diffusion Models
Jin Ma, Mohammed Aldeen, Christopher Salas +4
Object detection is fundamental to various real-world applications, such as security monitoring and surveillance video analysis. Despite their advancements, state-of-the-art object…
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…