将3D高斯点云重建自动转为可导航评测基准
NavArena: Automated Construction of Goal-Oriented Navigation Benchmarks from 3D Gaussian Splatting Reconstructions
- 用冻结的3DGS模型生成视角图像，结合密度与高度构建可达性地图
- 在2000多个场景中自动生成2220万条专家轨迹，支持闭环评估
- 适合需要大规模、可复现视觉导航评测的研究者使用
固定3D高斯点云（3DGS）重建能提供逼真的新视角图像，但缺乏可行走区域约束、有效目标和闭环评估协议，难以用于导航评测。本文提出NavArena，一个自动化框架，将固定3DGS重建转化为面向目标的视觉导航评测基准。该框架集成冻结的3DGS模型用于自我中心RGB-D渲染，基于高斯密度与高度统计构建占据代价图以支持可达性与碰撞查询，并从多视角开放词汇掩码中提取语义目标候选。这些组件支持目标导向导航任务的自动生成与统一闭环评估。在超过2000个场景中，NavArena生成了2220万条专家轨迹。空间与语义评估验证了所导出导航表示的有效性，策略滚动实验展示了统一评估协议的诊断价值。该方法实现了大规模3DGS重建上可扩展且可复现的导航评测，所有基准生成工具、评估协议及衍生资产将公开发布。
原文摘要 · Abstract (English)
Fixed 3D Gaussian Splatting (3DGS) reconstructions provide realistic novel views but lack the traversability constraints, valid goals, and closed-loop protocols required for navigation evaluation. We introduce NavArena, an automated framework that transforms fixed 3DGS reconstructions into benchmarks for goal-oriented visual navigation. NavArena integrates a frozen 3DGS model for egocentric RGB-D rendering, an occupancy costmap derived from Gaussian density and height statistics for reachability and collision queries, and semantic goal candidates lifted from multi-view open-vocabulary masks. These components support the automatic generation and unified closed-loop evaluation of goal-oriented navigation episodes. Across more than 2{,}000 scenes, NavArena generates 22.2 million expert trajectories. Spatial and semantic evaluations assess the derived navigation representations, while policy rollouts demonstrate the diagnostic value of the unified evaluation protocol. NavArena enables scalable and reproducible navigation evaluation on large-scale 3DGS reconstructions, and all benchmark-generation tools, evaluation protocols, and derived assets will be released publicly.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。