Papers
arxiv:2611.03228

AnchorComplete: Recovering Complete Scene Meshes from Partial Point Clouds

Published on Nov 2
· Submitted by
Ismail ElYamany
on Nov 5
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Abstract

AnchorComplete reconstructs complete scene meshes from partial point clouds by combining partial-point conditioning with metric-scale coarse-to-fine generation, improving reconstruction under sparse views.

Most image-based 3D reconstructors primarily recover visible surfaces, producing partial point clouds with large holes and leaving unobserved geometry unresolved. To address this limitation, we introduce AnchorComplete, a framework that reconstructs complete scene meshes from partial point clouds while preserving observed geometry and supporting scenes of varying scales. Building on TRELLIS.2, our method combines partial-point conditioning, which integrates global scene tokens with local spatial evidence to anchor generation to the input, and metric-scale coarse-to-fine generation, which progressively refines scene geometry within fixed-size windows while maintaining global structural consistency. Experiments on Replica and SCRREAM demonstrate that AnchorComplete consistently outperforms strong baselines in complete-scene reconstruction, particularly under sparse-view settings.

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TL;DR: AnchorComplete turns partial point clouds into complete scene meshes, preserves observed geometry, and scales from individual rooms to large multi-room scenes through metric-scale coarse-to-fine generation.

🎥Project Page: https://wrchen530.github.io/anchor-complete/
📄Paper: https://arxiv.org/abs/2611.03228

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