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Less Context, Better Geometry: Masked Geometric Encoder for Robust 3D Foundation Models

Paper recorded by Signals 4 on 2026-10-05 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-05 on arXiv · recorded by Signals 4 on 2026-10-06

Category: cs.CV · 计算机视觉 · first seen 2026-10-06

Abstract

Recent progress in 3D foundation models has enabled rapid 3D reconstruction and camera calibration by leveraging learned 3D priors from vast amount of spatial data. However, the all-to-all global attention design leads to quadratic complexity and limits long-sequence inference; unconstrained cross-view interactions also can propagate unreliable evidence from occluded or visually similar but geomet

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#354 most recent of 756 cs.CV papers we have recorded · ↑ newer: Anatomy-aware Fine-grained Multimodal Fusion for Laryngopharyngeal Can · ↓ older: Extending Dynamic World Surface Water Mapping to Sentinel-1 with Alpha
Cite this page: Less Context, Better Geometry: Masked Geometric Encoder for Robust 3D Foundation Models: the #354 most recent of 756 cs.CV papers we have recorded (as of 2026-10-05). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/less-context-better-geometry-masked-geometric-encoder-for-robust-3d-foundation-m.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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