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arXiv Computer Vision By Maximilian Jansen, Gasser Elazab, Praveen Kulkarni

Extrapolation Matters: Sparse-Only Depth Completion Beyond LiDAR Coverage

Read the original on arXiv Computer Vision →

The paper introduces a depth completion method that focuses on extrapolating depth beyond LiDAR coverage, a scenario often overlooked in current research. It uses a frozen monocular depth foundation model, aligns it with sparse LiDAR points, and refines the result with a module that fuses the prior and sparse anchors to produce dense metric depth. A novel high‑frequency normal‑consistency loss and a new evaluation protocol that separates LiDAR‑supported and beyond‑coverage regions are also presented, demonstrating strong accuracy in unobserved areas while maintaining performance where LiDAR data exists.

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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