English(EN) LiDAR-SHIELD: A Fully Dockerized Adversarial Robustness Assessment Framework for LiDAR-Based 3D Perception Models

新框架评估激光雷达3D感知模型的对抗鲁棒性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-31 04:00

研究人员开发了LiDAR-SHIELD，一个全面且Docker化的框架，用于评估基于激光雷达的3D感知模型的对抗鲁棒性。该框架通过三个轻量级的HTTP端点连接任何模型，简化了流程，无需手动设置环境和模型特定集成。LiDAR-SHIELD支持3D语义分割和物体检测任务，并包含一系列最先进的对抗攻击，以识别各种激光雷达骨干模型的漏洞。 AI

影响通过提供一种标准化的方法来测试激光雷达感知模型对抗对抗性攻击的能力，从而增强自动驾驶和机器人系统的安全性和可靠性。

排序理由该项目描述了一篇研究论文，其中详细介绍了一个用于评估激光雷达模型对抗鲁棒性的新框架。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Alexandros Gkillas, Ioulia Kapsali, Christos Anagnostopoulos, Aris S. Lalos · 2026-10-31 04:00

LiDAR-SHIELD：一个完全Docker化的激光雷达对抗性鲁棒性评估框架，用于基于激光雷达的3D感知模型

arXiv:2610.39848v1 Announce Type: cross Abstract: LiDAR-based 3D perception underpins autonomous driving and robotics, yet deploying these models safely requires stress-testing them against adversarial inputs before real-world use. Although state-of-the-art adversarial attacks ex…

本文如何被排名

报道来源 [1]

LiDAR-SHIELD：一个完全Docker化的激光雷达对抗性鲁棒性评估框架，用于基于激光雷达的3D感知模型

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