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arXiv Computer Vision By Jaafar Mahmoud, Arthur Movsesyan, Mikhail Iumanov, Sergey Kolyubin

DAVIO: Dense Monocular-Inertial SLAM with Feed-Forward Initialization and Pose-Conditioned Mapping

Read the original on arXiv Computer Vision →

DAVIO is a dense monocular‑inertial SLAM system that leverages a single multi‑view depth model (Depth Anything 3) for both initialization and mapping. It starts up quickly by solving a feature‑free linear system from a five‑image window and IMU pre‑integration, then uses a VIO filter whose metric poses condition the depth model during tracking. The system corrects residual scale along viewing rays, preserves metric baselines, and refines the map with a gravity‑preserving sub‑map graph, achieving earlier start‑up, lower localization error, and more accurate dense maps than state‑of‑the‑art feed‑forward mappers on both EuRoC and building‑scale ORI datasets.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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