Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models
Abstract
Vision-and-Language Navigation (VLN) has gained increasing attention over recent years and many approaches have emerged to advance their development. The remarkable achievements of foundation models have shaped the challenges and proposed methods for VLN research. In this survey, we provide a top-down review that adopts a principled framework for embodied planning and reasoning, and emphasizes the current methods and future opportunities leveraging foundation models to address VLN challenges. We hope our in-depth discussions could provide valuable resources and insights: on one hand, to document the progress and explore opportunities and potential roles for foundation models in this field, and on the other, to organize different challenges and solutions in VLN to foundation model researchers.
Cite
Text
Zhang et al. "Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models." Transactions on Machine Learning Research, 2024.Markdown
[Zhang et al. "Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models." Transactions on Machine Learning Research, 2024.](https://mlanthology.org/tmlr/2024/zhang2024tmlr-visionandlanguage/)BibTeX
@article{zhang2024tmlr-visionandlanguage,
title = {{Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models}},
author = {Zhang, Yue and Ma, Ziqiao and Li, Jialu and Qiao, Yanyuan and Wang, Zun and Chai, Joyce and Wu, Qi and Bansal, Mohit and Kordjamshidi, Parisa},
journal = {Transactions on Machine Learning Research},
year = {2024},
url = {https://mlanthology.org/tmlr/2024/zhang2024tmlr-visionandlanguage/}
}