GA-VLN builds a geometry-aware BEV representation from RGB-D inputs plus 3D foundation model features to deliver state-of-the-art vision-language navigation using only navigation data.
Monodream: Monocular vision-language navigation with panoramic dreaming
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UNVERDICTED 4representative citing papers
A monocular RGB-only aerial VLN framework outperforms baselines via prompt-guided multi-task learning, keyframe selection, and label reweighting on AerialVLN and OpenFly benchmarks.
Semantic progress reasoning predicts instruction-style advancement from visual history to guide policies, yielding state-of-the-art success and efficiency on R2R-CE and RxR-CE.
FutureNav proposes a 4B-scale VLM that jointly optimizes action prediction, inverse/forward dynamics, and future state generation for VLN and reports SOTA results on multiple benchmarks.
citing papers explorer
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GA-VLN: Geometry-Aware BEV Representation for Efficient Vision-Language Navigation
GA-VLN builds a geometry-aware BEV representation from RGB-D inputs plus 3D foundation model features to deliver state-of-the-art vision-language navigation using only navigation data.
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Aerial Vision-Language Navigation with a Unified Framework for Spatial, Temporal and Embodied Reasoning
A monocular RGB-only aerial VLN framework outperforms baselines via prompt-guided multi-task learning, keyframe selection, and label reweighting on AerialVLN and OpenFly benchmarks.
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Progress-Think: Semantic Progress Reasoning for Vision-Language Navigation
Semantic progress reasoning predicts instruction-style advancement from visual history to guide policies, yielding state-of-the-art success and efficiency on R2R-CE and RxR-CE.
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FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation
FutureNav proposes a 4B-scale VLM that jointly optimizes action prediction, inverse/forward dynamics, and future state generation for VLN and reports SOTA results on multiple benchmarks.