StopWatch: Goal Grounding for Object-goal Navigation
Pretrained VLMs bring rich world knowledge and semantic priors to object-goal navigation, and fine-tuning a VLM into a navigation policy has become a common recipe.
ProofPaper ↗
Key points
- Our diagnosis identifies goal grounding as the dominant failure.
- These policies explore well, yet often fail to notice that the goal is already in view or to estimate how far away it is.
- Explicit grounding substantially improves success and reaches state-of-the-art results on six benchmarks across three scene collections.
- Our work points to goal grounding as a missing piece of object-goal navigation and offers a simple and effective solution to the task.
Sources (2)
- [1]StopWatch: Goal Grounding for Object-goal NavigationHugging Face Daily Papers · Oct 16, 12:00 AM
Pretrained VLMs bring rich world knowledge and semantic priors to object-goal navigation, and fine-tuning a VLM into a navigation policy has become a common recipe.
Our diagnosis identifies goal grounding as the dominant failure.
- [2]StopWatch: Goal Grounding for Object-goal NavigationarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 16, 05:57 PM · same content
Extractive summary: sentences quoted from the sources.
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