FINE: Future-Informed Navigation Encoding for Data-Efficient Vision-Language Navigation
cs.RO, cs.CV
Submitted: 2026-09-26
Updated: 2026-09-26
Project page: https://finevln.github.io
Terminology
Sources
- NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation
- Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Tasks
- StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling
- FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation
- VLN-Zero: Rapid Exploration and Cache-Enabled Neurosymbolic Vision-Language Planning for Zero-Shot Transfer in Robot Navigation
- Sparse Video Generation Propels Real-World Beyond-the-View Vision-Language Navigation
- Joint On-and-Off Policy Learning for Vision-and-Language Navigation
- Turning Adaptation into Assets: Cross-Domain Bridging for Online Vision-Language Navigation
- Matterport3D: Learning from RGB-D Data in Indoor Environments
- Nano World Models: A Minimalist Implementation of Future Video Prediction
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