# AirSim360: A Panoramic Simulation Platform within Drone View

arXiv: https://arxiv.org/abs/2512.02009 · HTML: https://mlsanity.com/paper/2512.02009/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 33 of its 59 references that are in the map.
- First posted on arXiv 1 Dec 2025.

## Builds on (most cited first, 30 of 33)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [nuScenes: A multimodal dataset for autonomous driving](https://mlsanity.com/paper/1903.11027/) (2019)
- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [Masked-attention Mask Transformer for Universal Image Segmentation](https://mlsanity.com/paper/2112.01527/) (2021)
- [Matterport3D: Learning from RGB-D Data in Indoor Environments](https://mlsanity.com/paper/1709.06158/) (2017)
- [Semantic Understanding of Scenes through the ADE20K Dataset](https://mlsanity.com/paper/1608.05442/) (2016)
- [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://mlsanity.com/paper/1711.07280/) (2017)
- [AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles](https://mlsanity.com/paper/1705.05065/) (2017)
- [Joint 2D-3D-Semantic Data for Indoor Scene Understanding](https://mlsanity.com/paper/1702.01105/) (2017)
- [Habitat 3.0: A Co-Habitat for Humans, Avatars and Robots](https://mlsanity.com/paper/2310.13724/) (2023)
- [A Self-Supervised Descriptor for Image Copy Detection](https://mlsanity.com/paper/2202.10261/) (2022)
- [BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation](https://mlsanity.com/paper/2403.09227/) (2024)
- [AerialVLN: Vision-and-Language Navigation for UAVs](https://mlsanity.com/paper/2308.06735/) (2023)
- [Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction](https://mlsanity.com/paper/1809.00786/) (2018)
- [Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology](https://mlsanity.com/paper/2410.07087/) (2024)
- [High-Quality Entity Segmentation](https://mlsanity.com/paper/2211.05776/) (2022)
- [Open-World Entity Segmentation](https://mlsanity.com/paper/2107.14228/) (2021)
- [A Survey on Vision-Language-Action Models for Autonomous Driving](https://mlsanity.com/paper/2506.24044/) (2025)
- [Deep Sky Modeling for Single Image Outdoor Lighting Estimation](https://mlsanity.com/paper/1905.03897/) (2019)
- [Capturing Omni-Range Context for Omnidirectional Segmentation](https://mlsanity.com/paper/2103.05687/) (2021)
- [Aerial Vision-and-Dialog Navigation](https://mlsanity.com/paper/2205.12219/) (2022)
- [Openfly: A comprehensive platform for aerial vision-language navigation](https://mlsanity.com/paper/2502.18041/) (2025)
- [Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach](https://mlsanity.com/paper/1710.10755/) (2017)
- [UAVScenes: A Multi-Modal Dataset for UAVs](https://mlsanity.com/paper/2507.22412/) (2025)
- [360-Indoor: Towards Learning Real-World Objects in 360deg Indoor Equirectangular Images](https://mlsanity.com/paper/1910.01712/) (2019)
- [UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI](https://mlsanity.com/paper/2412.20977/) (2024)
- [One Flight Over the Gap: A Survey from Perspective to Panoramic Vision](https://mlsanity.com/paper/2509.04444/) (2025)
- [DiT360: High-Fidelity Panoramic Image Generation via Hybrid Training](https://mlsanity.com/paper/2510.11712/) (2025)
- [Open Panoramic Segmentation](https://mlsanity.com/paper/2407.02685/) (2024)
- [Cosys-AirSim: A Real-Time Simulation Framework Expanded for Complex Industrial Applications](https://mlsanity.com/paper/2303.13381/) (2023)

## Built on by (most cited first, 12 of 12)

- [Depth Any Panoramas: A Foundation Model for Panoramic Depth Estimation](https://mlsanity.com/paper/2512.16913/) (2025)
- [MemoBench: Benchmarking World Modeling in Dynamically Changing Environments](https://mlsanity.com/paper/2606.27537/) (2026)
- [SimWorlds: A Multi-Agent System for Dynamic 3D Scene Creation](https://mlsanity.com/paper/2607.01766/) (2026)
- [PanoWorld: Towards Spatial Supersensing in 360^circ Panorama World](https://mlsanity.com/paper/2605.13169/) (2026)
- [PanoWorld: Real-World Panoramic Generation](https://mlsanity.com/paper/2607.09661/) (2026)
- [Fly360: Omnidirectional Obstacle Avoidance within Drone View](https://mlsanity.com/paper/2603.06573/) (2026)
- [UniSHARP: Universal Sharp Monocular View Synthesis](https://mlsanity.com/paper/2606.07514/) (2026)
- [See-and-Reach: Precise Vision-Language Navigation for UAVs within the Field of View](https://mlsanity.com/paper/2606.20045/) (2026)
- [WorldRover: A Scalable Synthetic Video Data Engine for World Exploration with Rich Annotations](https://mlsanity.com/paper/2608.15659/) (2026)
- [Look Up and Look Back: Hidden Attention and Latent Orientation in a Frozen Foundation Model for Panoramic SLAM](https://mlsanity.com/paper/2608.00925/) (2026)
- [Zero-Shot UAV Navigation in Forests via Relightable 3D Gaussian Splatting](https://mlsanity.com/paper/2602.07101/) (2026)
- [Geometry and Gradient-based Partitioning for Panoramic Outdoor Reconstruction](https://mlsanity.com/paper/2607.08769/) (2026)

## Abstract (arXiv)

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.