Abstract
Neural Radiance Field (NeRF) has garnered significant attention from both academia and industry due to its intrinsic advantages, particularly its implicit representation and novel view synthesis capabilities. With the rapid advancements in deep learning, a multitude of methods have emerged to explore the potential applications of NeRF in the domain of Autonomous Driving (AD). However, a conspicuous void is apparent within the current literature. To bridge this gap, this paper conducts a comprehensive survey of NeRF's applications in the context of AD. Our survey is structured to categorize NeRF's applications in Autonomous Driving (AD), specifically encompassing perception, 3D reconstruction, simultaneous localization and mapping (SLAM), and simulation. We delve into in-depth analysis and summarize the findings for each application category, and conclude by providing insights and discussions on future directions in this field. We hope this paper serves as a comprehensive reference for researchers in this domain. To the best of our knowledge, this is the first survey specifically focused on the applications of NeRF in the Autonomous Driving domain.
Abstract (translated)
Neural Radiance Field（NeRF）因其固有优势，特别是其隐式表示和新视图合成能力，在学术界和产业界都引起了显著关注。随着深度学习的快速发展，为探索NeRF在自动驾驶（AD）领域的潜在应用，已经涌现出了许多方法。然而，当前文献中显然存在一个明显的空白。为了填补这一空白，本文对NeRF在AD领域中的应用进行全面调查。我们的调查旨在对NeRF的每个应用进行分类，包括感知、3D重建、同时定位与映射（SLAM）和仿真。我们深入分析每个应用类别，并总结了每个应用类别的发现。最后，我们提供了关于未来该领域的发展方向以及见解和讨论。我们希望，本文将成为该领域研究人员的全面参考。据我们所知，这是第一部专门关注NeRF在AD领域应用的调查。
URL
https://arxiv.org/abs/2404.13816
