Papers with Vision-language navigation
Visual-Language Navigation Pretraining via Prompt-based Environmental Self-exploration (2022.acl-long)
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| Challenge: | Existing methods of fine-tuning vision-language navigation models require extra human-labeled data and lack self-exploration capabilities in environments. |
| Approach: | They propose a method that can self-explore environments without human labeling . they use a large-scale cross-modal pretrained model to build an in-domain dataset . |
| Outcome: | The proposed model can self-explore environments without human labeling without human supervision and generates structured instructions without human intervention. |
MapNav: A Novel Memory Representation via Annotated Semantic Maps for VLM-based Vision-and-Language Navigation (2025.acl-long)
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Lingfeng Zhang, Xiaoshuai Hao, Qinwen Xu, Qiang Zhang, Xinyao Zhang, Pengwei Wang, Jing Zhang, Zhongyuan Wang, Shanghang Zhang, Renjing Xu
| Challenge: | Vision-language navigation (VLN) is a key task in Embodied AI . traditional approaches rely on historical observations as spatio-temporal contexts for decision making . |
| Approach: | They propose a vision-language navigation model that leverages an annotation system to replace historical frames. |
| Outcome: | The proposed model can be used as a new memory representation method in vision-language navigation . it can be applied to simulated and real-world environments, and it is validated by experiments . |