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SURE-Map: Self-Correcting Streaming Geometric Foundation Model

Paper recorded by Signals 4 on 2026-09-14 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15

Category: cs.CV · 计算机视觉 · first seen 2026-09-15

Abstract

Streaming geometric foundation models are emerging as a compelling alternative to SLAM systems. Yet this streaming nature introduces a fundamental issue: each prediction is made from limited context, which is vulnerable to dynamic objects and weak textures. Small local errors accumulate into severe geometric distortion and long-horizon scale drift. We argue that reliable streaming reconstruction r

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#49 most recent of 237 cs.CV papers we have recorded · ↑ newer: VC-Attention: Value Smoothing and Softmax Casting for Low-bit Attentio · ↓ older: TopoRig: Topology-Agnostic Facial Rigging via Multi-Source Supervision
Cite this page: SURE-Map: Self-Correcting Streaming Geometric Foundation Model: the #49 most recent of 237 cs.CV papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/sure-map-self-correcting-streaming-geometric-foundation-model.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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