Vision Transformers are reshaping the landscape of Autonomous Driving by leveraging their success in Natural Language Processing. They excel in tasks like object detection, lane detection, and segmentation, providing a comprehensive understanding of dynamic driving environments. The survey explores the structural components of Transformers, such as self-attention and multi-head attention mechanisms. It delves into the applications of Vision Transformers in 3D and 2D perception tasks, highlighting their impact on autonomous vehicle technology. Additionally, it discusses challenges, trends, and future directions for Vision Transformers in Autonomous Driving.
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by Quoc-Vinh La... alle arxiv.org 03-13-2024
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