RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping
Road surface mapping plays a crucial role in autonomous driving, supporting high-definition map generation, lane-level perception, and automatic road annotation. Recent mesh-based road surface reconstruction methods have shown promising results, but they still suffer from limited reconstruction quality and high optimization cost, especially in large-scale driving scenarios. To address these limitations, we propose ROADGS-T, a robust and efficient large-scale road surface mapping framework based on adaptive meshgrid Gaussian representation. Specifically, we model the road surface by placing 2D
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- FuzzyOverlapping authors or contributors · 62%bytedance/deer-flow →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%ray-project/ray →
“Shared author/contributor keys: wang”
- LinkedLinked via arxiv author · 85%Tianchen Deng →
“RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping”
- LinkedLinked via arxiv author · 85%Zhiheng Feng →
“RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping”
- LinkedLinked via arxiv author · 85%Wenhua Wu →
“RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping”
- LinkedLinked via arxiv author · 85%Ziming Li →
“RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping”
- LinkedLinked via arxiv author · 85%Siting Zhu →
“RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping”
- LinkedLinked via arxiv author · 85%Hesheng Wang →
“RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping”