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LangStreet: Persistent Language Fields for Anchor-Decoded Street Gaussians

arxiv.org/abs/2609.11616

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Updated 4 h ago · first seen 11 Sept 2026

paper_01M294H2CT7E2171GRA0MWB4JE

Published
11 Sept 2026
T1 · 4 h ago
arXiv
2609.11616
T1 · 4 h ago
Category
cs.CV
T1 · 4 h ago

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https://arxiv.org/abs/2609.11616currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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Language Gaussian fields implicitly assume that the primitive carrying semantics remains identifiable across views. This assumption breaks in scalable anchor-decoded representations, where persistent anchors generate view-conditioned child Gaussians whose geometry and appearance vary with the camera. We introduce Ours, a persistent language field for such structured Gaussian scenes. Our key idea is semantic ownership: transient children route observations, while persistent decoder slots and their parent anchors own the language field. We use alpha-compositing responsibilities to accumulate additive directional evidence at slots; these statistics marginalize exactly to anchors. We then complete weakly supported slots with anchor-aligned evidence while preserving the anchor direction, and represent slot detail through low-rank residuals in anchor-relative semantic coordinates. Our primary model, Ours (base), stores anchor features together with compact slot residuals. Ours (light) retains only anchor features, whereas Ours (max) stores the full-dimensional completed slot features explicitly. Without scene-specific semantic optimization, Ours (base) nearly matches Ours (max) across KITTI, Virtual KITTI, and Waymo. On KITTI, it achieves 34.19 2D mIoU with a 2.72 GiB effective feature footprint, compared with 34.20 mIoU and 12.90 GiB for Ours (max). The same accuracy-storage trend holds on Virtual KITTI and Waymo. These results show that language fields on view-conditioned splats require persistent semantic ownership, conserved evidence, and a hierarchy that balances stability, detail, and representation cost. Our code, checkpoints, and benchmark suite will be publicly available.currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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newcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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2609.11616currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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Runyi Yang, Deheng Zhang, Xiaoye Wang, Mengjiao Ma, Lei Sun, Kanzhi Wu, Ajad Chhatkuli, Luc Van Gool, Danda Pani PaudelcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.CVcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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https://arxiv.org/pdf/2609.11616currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.CVcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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11 Sept 2026currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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