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Computer Science > Computer Vision and Pattern Recognition

arXiv:2203.12667 (cs)
[Submitted on 22 Mar 2022 (v1), last revised 3 Jun 2022 (this version, v3)]

Title:Vision-and-Language Navigation: A Survey of Tasks, Methods, and Future Directions

Authors:Jing Gu, Eliana Stefani, Qi Wu, Jesse Thomason, Xin Eric Wang
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Abstract:A long-term goal of AI research is to build intelligent agents that can communicate with humans in natural language, perceive the environment, and perform real-world tasks. Vision-and-Language Navigation (VLN) is a fundamental and interdisciplinary research topic towards this goal, and receives increasing attention from natural language processing, computer vision, robotics, and machine learning communities. In this paper, we review contemporary studies in the emerging field of VLN, covering tasks, evaluation metrics, methods, etc. Through structured analysis of current progress and challenges, we highlight the limitations of current VLN and opportunities for future work. This paper serves as a thorough reference for the VLN research community.
Comments: 19 pages. Accepted to ACL 2022
Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
Cite as: arXiv:2203.12667 [cs.CV]
  (or arXiv:2203.12667v3 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2203.12667
Journal reference: ACL 2022, Long, pages 7606,7623, Dublin, Ireland. Association for Computational Linguistics
Related DOI: https://doi.org/10.18653/v1/2022.acl-long.524

Submission history

From: Jing Gu [view email]
[v1] Tue, 22 Mar 2022 16:58:10 UTC (2,075 KB)
[v2] Tue, 29 Mar 2022 17:45:40 UTC (2,077 KB)
[v3] Fri, 3 Jun 2022 23:12:40 UTC (2,078 KB)
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