June 7, 2024, 4:48 a.m. | Jixiang Wan, Xudong Zhang, Shuzhou Dong, Yuwei Zhang, Yuchen Yang, Ruoxi Wu, Ye Jiang, Jijunnan Li, Jinquan Lin, Ming Yang

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.03835v1 Announce Type: new
Abstract: Accurate and robust localization remains a significant challenge for autonomous vehicles. The cost of sensors and limitations in local computational efficiency make it difficult to scale to large commercial applications. Traditional vision-based approaches focus on texture features that are susceptible to changes in lighting, season, perspective, and appearance. Additionally, the large storage size of maps with descriptors and complex optimization processes hinder system performance. To balance efficiency and accuracy, we propose a novel lightweight visual …

abstract applications arxiv autonomous autonomous vehicles challenge commercial computational cost cs.cv cs.ro efficiency features focus lighting limitations localization map perspective robust scale semantics sensors texture type vehicles vision

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