Learning from Unlabeled 3D Environments for Vision-and-Language Navigation

@article{Chen2022LearningFU,
  title={Learning from Unlabeled 3D Environments for Vision-and-Language Navigation},
  author={Shizhe Chen and Pierre-Louis Guhur and Makarand Tapaswi and Cordelia Schmid and Ivan Laptev},
  journal={ArXiv},
  year={2022},
  volume={abs/2208.11781}
}
. In vision-and-language navigation (VLN), an embodied agent is required to navigate in realistic 3D environments following natural language instructions. One major bottleneck for existing VLN approaches is the lack of sufficient training data, resulting in unsatisfactory generalization to unseen environments. While VLN data is typically collected manually, such an approach is expensive and prevents scalability. In this work, we address the data scarcity issue by proposing to automatically… 

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