Papers › Airbert: In-domain Pretraining for Vision-and-Language Navigation
Airbert: In-domain Pretraining for Vision-and-Language Navigation
Pierre-Louis Guhur, Makarand Tapaswi, ShiZhe Chen, Ivan Laptev, Cordelia Schmid
Vision-and-language navigation (VLN) aims to enable embodied agents to navigate in realistic environments using natural language instructions. Given the scarcity of domain-specific training data and the high diversity of image and language inputs, the generalization of VLN agents to unseen environments remains challenging. Recent methods explore pretraining to improve generalization, however, the use of generic image-caption datasets or existing small-scale VLN environments is suboptimal and results in limited improvements. In this work, we introduce BnB, a large-scale and diverse in-domain VLN dataset. We first collect image-caption (IC) pairs from hundreds of thousands of listings from online rental marketplaces. Using IC pairs we next propose automatic strategies to generate millions of VLN path-instruction (PI) pairs. We further propose a shuffling loss that improves the learning of temporal order inside PI pairs. We use BnB pretrain our Airbert model that can be adapted to discriminative and generative settings and show that it outperforms state of the art for Room-to-Room (R2R) navigation and Remote Referring Expression (REVERIE) benchmarks. Moreover, our in-domain pretraining significantly increases performance on a challenging few-shot VLN evaluation, where we train the model only on VLN instructions from a few houses.
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Code
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Vision and Language Navigation | VLN Challenge | Airbert | error | 2.58 | #3 of 145 | Archive leaderboard | report |
| Vision and Language Navigation | VLN Challenge | Airbert | length | 686.54 | #3 of 145 | Archive leaderboard | report |
| Vision and Language Navigation | VLN Challenge | Airbert | oracle success | 0.99 | #3 of 145 | Archive leaderboard | report |
| Vision and Language Navigation | VLN Challenge | Airbert | spl | 0.01 | #3 of 145 | Archive leaderboard | report |
| Vision and Language Navigation | VLN Challenge | Airbert | success | 0.78 | #3 of 145 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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