论文标题
从看见到移动：有关视觉室内导航（VIN）学习的调查
From Seeing to Moving: A Survey on Learning for Visual Indoor Navigation (VIN)
论文作者
论文摘要
视觉室内导航（VIN）任务引起了数据驱动的机器学习社区的越来越多的关注，尤其是在基于学习的方法中最近报道的成功。由于这项任务的先天复杂性，研究人员尝试从各种不同角度解决问题，其全部范围尚未在总体报告中捕获。这项调查首先总结了VIN任务的基于学习的方法的代表性工作，然后确定并讨论了阻碍VIN绩效的问题，并激发了值得探索社区的这些关键领域的未来研究。
Visual Indoor Navigation (VIN) task has drawn increasing attention from the data-driven machine learning communities especially with the recently reported success from learning-based methods. Due to the innate complexity of this task, researchers have tried approaching the problem from a variety of different angles, the full scope of which has not yet been captured within an overarching report. This survey first summarizes the representative work of learning-based approaches for the VIN task and then identifies and discusses lingering issues impeding the VIN performance, as well as motivates future research in these key areas worth exploring for the community.
