Vision-and-Language Navigation: A Survey of Tasks, Methods, and Future Directions (2022.acl-long)
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| Challenge: | Vision-and-Language Navigation (VLN) is a research topic that is gaining attention in the field of artificial intelligence. |
| Approach: | They propose to build an embodied agent that can communicate with humans in natural language and navigate in real 3D environments. |
| Outcome: | This paper reviews current studies in the emerging field of vision-and-language navigation . it highlights limitations and opportunities for future work . |
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Wanrong Zhu, Yuankai Qi, Pradyumna Narayana, Kazoo Sone, Sugato Basu, Xin Wang, Qi Wu, Miguel Eckstein, William Yang Wang
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| Challenge: | Recent work on visual-grounded navigation has focused on indoor scenarios with sharp drops in performance when testing on unseen data. |
| Approach: | They focus on visual agent navigation in outdoor scenarios with panorama images . they find that most gain in outdoor VLN on unseen data is due to specific features . |
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GesNavi: Gesture-guided Outdoor Vision-and-Language Navigation (2024.eacl-srw)
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| Challenge: | Existing datasets for outdoor Vision-and-Language Navigation (VLN) tasks do not include verbal instructions for communicating with mobility. |
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| Challenge: | Vision and language navigation (VLN) is a challenging task towards the creation of embodied agents. |
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Connecting Language and Vision to Actions (P18-5)
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| Challenge: | Recent advances in language and vision have made incredible progress in describing images and interacting with visual content in a physical or embodied environment. |
| Approach: | This tutorial will provide an overview of the growing number of multimodal tasks and datasets that combine textual and visual understanding. |
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Action Inference for Destination Prediction in Vision-and-Language Navigation (2024.acl-srw)
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| Challenge: | Existing work on vision-and-language navigation focuses on spatial reasoning and semantic grounding of visual information, but there is still scope for improvement. |
| Approach: | They propose a VLN task of destination prediction for picking up a pedestrian that requires action inference from a crowd-sourced dataset. |
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CLEAR: Improving Vision-Language Navigation with Cross-Lingual, Environment-Agnostic Representations (2022.findings-naacl)
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| Challenge: | Using multilingual instructions to learn a better cross-lingual representation is challenging for multilingual agents. |
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Language-Aligned Waypoint (LAW) Supervision for Vision-and-Language Navigation in Continuous Environments (2021.emnlp-main)
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| Challenge: | Prior work on Vision-and-Language Navigation (VLN) tasks do not measure how much of a language instruction the agent is able to follow. |
| Approach: | They propose a language-aligned supervision scheme that measures the number of sub-instructions the agent has completed during navigation. |
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Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation (P19-1)
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| Challenge: | Existing models that ground language into visual appearance and route structure are outperforming their visual counterparts in unseen new environments. |
| Approach: | They propose to decompose the grounding procedure into a set of expert models with access to different modalities and ensemble them at prediction time. |
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Masked Path Modeling for Vision-and-Language Navigation (2023.findings-emnlp)
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| Challenge: | A major challenge in vision-and-language navigation is the limited available training data, which hinders the models’ ability to generalize effectively. |
| Approach: | They propose a masked path modeling objective that pretrains an agent using self-collected data for subsequent navigation tasks. |
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