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Robustness Evaluation of HD Map Constructors under Sensor Corruptions for Autonomous Driving
The paper focuses on evaluating the robustness of HD map constructors under various sensor corruptions using a comprehensive benchmark called MapBench. It highlights the vulnerability of existing methods to real-world challenges and suggests the importance of advanced data augmentation techniques and new network architectures to enhance robustness for autonomous driving applications.
Read full paper: https://arxiv.org/abs/2406.12214
Tags: Autonomous Driving, Computer Vision, AI Safety
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By Arjun SrivastavaThe paper focuses on evaluating the robustness of HD map constructors under various sensor corruptions using a comprehensive benchmark called MapBench. It highlights the vulnerability of existing methods to real-world challenges and suggests the importance of advanced data augmentation techniques and new network architectures to enhance robustness for autonomous driving applications.
Read full paper: https://arxiv.org/abs/2406.12214
Tags: Autonomous Driving, Computer Vision, AI Safety