POINav-Bench provides the first high-fidelity real-world benchmark for POI-goal VLN using 3DGS reconstructions of 126k m² with 163 POIs, supported by a Brain-Action framework and 70K real signage-entrance dataset.
End-to-end (instance)-image goal navigation through correspondence as an emergent phenomenon.arXiv preprint arXiv:2309.16634
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.RO 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
FeudalNav decomposes visual navigation into hierarchical levels with a visual-similarity latent memory, delivering competitive Habitat AI results without any odometry.
Proposes a hierarchical navigation framework with viewpoint-aware action nodes, cross-graph memory, and learning-based policy for quadrotor InstanceImageNav, claiming improvements over baselines in simulation and real-world validation.
citing papers explorer
-
POINav: Benchmarking and Enhancing Final-Meters Arrival in Real-World Vision-Language Navigation
POINav-Bench provides the first high-fidelity real-world benchmark for POI-goal VLN using 3DGS reconstructions of 126k m² with 163 POIs, supported by a Brain-Action framework and 70K real signage-entrance dataset.
-
FeudalNav: A Simple Framework for Visual Navigation
FeudalNav decomposes visual navigation into hierarchical levels with a visual-similarity latent memory, delivering competitive Habitat AI results without any odometry.
-
Flying to Image-Specified Objects: 3D Quadrotor Navigation via Cross-Graph Memory and Viewpoint Planning
Proposes a hierarchical navigation framework with viewpoint-aware action nodes, cross-graph memory, and learning-based policy for quadrotor InstanceImageNav, claiming improvements over baselines in simulation and real-world validation.