AirSim360用无人机视角生成全景数据，助力空间智能研究。
AirSim360: A Panoramic Simulation Platform within Drone View
- 基于无人机视角构建全景数据生成平台，支持像素级理解。
- 采集超6万张全景样本，覆盖多种导航与感知任务。
- 首个系统化建模4D全景世界的仿真平台，适合视觉与自动驾驶研究。
全景多向理解领域正推动空间智能发展，但大规模多样数据的缺乏仍是主要瓶颈。本文提出AirSim360，一个基于无人机视角的全景数据仿真平台，支持广泛场景采样。该平台聚焦三大核心：像素级几何、语义与实体理解的渲染对齐数据与标注范式；交互式行人感知系统以建模人类行为；自动化轨迹生成机制支持导航任务。我们共收集超过6万张全景样本，并在多个任务上开展大量实验，验证其有效性。与现有模拟器不同，本工作首次在全景设定下系统性建模4D真实世界。整个平台（含工具包、插件及数据集）将公开发布于 https://insta360-research-team.github.io/AirSim360-website。
原文摘要 · Abstract (English)
The field of 360-degree omnidirectional understanding has been receiving increasing attention for advancing spatial intelligence. However, the lack of large-scale and diverse data remains a major limitation. In this work, we propose AirSim360, a simulation platform for omnidirectional data from aerial viewpoints, enabling wide-ranging scene sampling with drones. Specifically, AirSim360 focuses on three key aspects: a render-aligned data and labeling paradigm for pixel-level geometric, semantic, and entity-level understanding; an interactive pedestrian-aware system for modeling human behavior; and an automated trajectory generation paradigm to support navigation tasks. Furthermore, we collect more than 60K panoramic samples and conduct extensive experiments across various tasks to demonstrate the effectiveness of our simulator. Unlike existing simulators, our work is the first to systematically model the 4D real world under an omnidirectional setting. The entire platform, including the toolkit, plugins, and collected datasets, will be made publicly available at https://insta360-research-team.github.io/AirSim360-website.
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