# One Flight Over the Gap: A Survey from Perspective to Panoramic Vision

arXiv: https://arxiv.org/abs/2509.04444 · HTML: https://mlsanity.com/paper/2509.04444/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- Builds on 66 of its 389 references that are in the map.
- First posted on arXiv 4 Sep 2025.

## Builds on (most cited first, 30 of 66)

- [SAM 2: Segment Anything in Images and Videos](https://mlsanity.com/paper/2408.00714/) (2024)
- [Joint 2D-3D-Semantic Data for Indoor Scene Understanding](https://mlsanity.com/paper/1702.01105/) (2017)
- [HunyuanWorld 1.0: Generating Immersive, Explorable, and Interactive 3D Worlds from Words or Pixels](https://mlsanity.com/paper/2507.21809/) (2025)
- [LayerPano3D: Layered 3D Panorama for Hyper-Immersive Scene Generation](https://mlsanity.com/paper/2408.13252/) (2024)
- [CAT2000: A Large Scale Fixation Dataset for Boosting Saliency Research](https://mlsanity.com/paper/1505.03581/) (2015)
- [PanoDiffusion: 360-degree Panorama Outpainting via Diffusion](https://mlsanity.com/paper/2307.03177/) (2023)
- [Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion Models](https://mlsanity.com/paper/2311.13141/) (2023)
- [360-Degree Panorama Generation from Few Unregistered NFoV Images](https://mlsanity.com/paper/2308.14686/) (2023)
- [360-GS: Layout-guided Panoramic Gaussian Splatting For Indoor Roaming](https://mlsanity.com/paper/2402.00763/) (2024)
- [Matrix-3D: Omnidirectional Explorable 3D World Generation](https://mlsanity.com/paper/2508.08086/) (2025)
- [RTMV: A Ray-Traced Multi-View Synthetic Dataset for Novel View Synthesis](https://mlsanity.com/paper/2205.07058/) (2022)
- [CC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion](https://mlsanity.com/paper/2212.01247/) (2022)
- [OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation](https://mlsanity.com/paper/2503.07098/) (2025)
- [SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation](https://mlsanity.com/paper/2306.03403/) (2023)
- [HoloDreamer: Holistic 3D Panoramic World Generation from Text Descriptions](https://mlsanity.com/paper/2407.15187/) (2024)
- [SceneDreamer360: Text-Driven 3D-Consistent Scene Generation with Panoramic Gaussian Splatting](https://mlsanity.com/paper/2408.13711/) (2024)
- [Are Multimodal Large Language Models Ready for Omnidirectional Spatial Reasoning?](https://mlsanity.com/paper/2505.11907/) (2025)
- [PanoWan: Lifting Diffusion Video Generation Models to 360deg with Latitude/Longitude-aware Mechanisms](https://mlsanity.com/paper/2505.22016/) (2025)
- [OmniGS: Fast Radiance Field Reconstruction using Omnidirectional Gaussian Splatting](https://mlsanity.com/paper/2404.03202/) (2024)
- [360Roam: Real-Time Indoor Roaming Using Geometry-Aware 360^circ Radiance Fields](https://mlsanity.com/paper/2208.02705/) (2022)
- [HumanoidPano: Hybrid Spherical Panoramic-LiDAR Cross-Modal Perception for Humanoid Robots](https://mlsanity.com/paper/2503.09010/) (2025)
- [VideoPanda: Video Panoramic Diffusion with Multi-view Attention](https://mlsanity.com/paper/2504.11389/) (2025)
- [Towards Omnidirectional Reasoning with 360-R1: A Dataset, Benchmark, and GRPO-based Method](https://mlsanity.com/paper/2505.14197/) (2025)
- [DreamCube: 3D Panorama Generation via Multi-plane Synchronization](https://mlsanity.com/paper/2506.17206/) (2025)
- [Manhattan Room Layout Reconstruction from a Single 360 image: A Comparative Study of State-of-the-art Methods](https://mlsanity.com/paper/1910.04099/) (2019)
- [Casual Indoor HDR Radiance Capture from Omnidirectional Images](https://mlsanity.com/paper/2208.07903/) (2022)
- [3D Scene Geometry Estimation from 360^circ Imagery: A Survey](https://mlsanity.com/paper/2401.09252/) (2024)
- [GoodSAM++: Bridging Domain and Capacity Gaps via Segment Anything Model for Panoramic Semantic Segmentation](https://mlsanity.com/paper/2408.09115/) (2024)
- [Para-Lane: Multi-Lane Dataset Registering Parallel Scans for Benchmarking Novel View Synthesis](https://mlsanity.com/paper/2502.15635/) (2025)
- [Omni2: Unifying Omnidirectional Image Generation and Editing in an Omni Model](https://mlsanity.com/paper/2504.11379/) (2025)

## Built on by (most cited first, 26 of 26)

- [Depth Any Panoramas: A Foundation Model for Panoramic Depth Estimation](https://mlsanity.com/paper/2512.16913/) (2025)
- [DiT360: High-Fidelity Panoramic Image Generation via Hybrid Training](https://mlsanity.com/paper/2510.11712/) (2025)
- [OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation](https://mlsanity.com/paper/2603.30045/) (2026)
- [AirSim360: A Panoramic Simulation Platform within Drone View](https://mlsanity.com/paper/2512.02009/) (2025)
- [ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modeling](https://mlsanity.com/paper/2603.02697/) (2026)
- [CubeComposer: Spatio-Temporal Autoregressive 4K 360deg Video Generation from Perspective Video](https://mlsanity.com/paper/2603.04291/) (2026)
- [OneOcc: Semantic Occupancy Prediction for Legged Robots with a Single Panoramic Camera](https://mlsanity.com/paper/2511.03571/) (2025)
- [Panoramic Multimodal Semantic Occupancy Prediction for Quadruped Robots](https://mlsanity.com/paper/2603.13108/) (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)
- [OmniTrack++: Omnidirectional Multi-Object Tracking by Learning Large-FoV Trajectory Feedback](https://mlsanity.com/paper/2511.00510/) (2025)
- [Fly360: Omnidirectional Obstacle Avoidance within Drone View](https://mlsanity.com/paper/2603.06573/) (2026)
- [O3N: Omnidirectional Open-Vocabulary Occupancy Prediction for Embodied Intelligent Robotics](https://mlsanity.com/paper/2603.12144/) (2026)
- [UniSHARP: Universal Sharp Monocular View Synthesis](https://mlsanity.com/paper/2606.07514/) (2026)
- [Seeing Beyond: Extrapolative Domain Adaptive Panoramic Segmentation](https://mlsanity.com/paper/2603.15475/) (2026)
- [Panoramic Affordance Prediction](https://mlsanity.com/paper/2603.15558/) (2026)
- [Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling](https://mlsanity.com/paper/2606.27745/) (2026)
- [Spheriverse: 3D Scene Understanding from Spherical Observations in the Wild](https://mlsanity.com/paper/2609.09012/) (2026)
- [PAGCNet: A Pose-Aware and Geometry Constrained Framework for Panoramic Depth Estimation](https://mlsanity.com/paper/2510.07817/) (2025)
- [World-Shaper: A Unified Framework for 360deg Panoramic Editing](https://mlsanity.com/paper/2602.00265/) (2026)
- [Pano360: Perspective to Panoramic Vision with Geometric Consistency](https://mlsanity.com/paper/2603.12013/) (2026)
- [Towards Accurate Single Panoramic 3D Detection: A Semantic Gaussian Centric Approach](https://mlsanity.com/paper/2605.14601/) (2026)
- [SHERPA: Seam-aware Harmonized ERP Adaptation for Open-Domain 360^circ Panorama Generation](https://mlsanity.com/paper/2606.12213/) (2026)
- [CylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object Tracking](https://mlsanity.com/paper/2606.30097/) (2026)
- [OmniCoT: A Benchmark for Global and Multi-Step Panoramic Reasoning](https://mlsanity.com/paper/2606.30378/) (2026)
- [Geometry and Gradient-based Partitioning for Panoramic Outdoor Reconstruction](https://mlsanity.com/paper/2607.08769/) (2026)

## Abstract (arXiv)

Driven by the demand for spatial intelligence and holistic scene perception, omnidirectional images (ODIs), which provide a complete 360textdegree field of view, are receiving growing attention across diverse applications such as virtual reality, autonomous driving, and embodied robotics. Despite their unique characteristics, ODIs exhibit remarkable differences from perspective images in geometric projection, spatial distribution, and boundary continuity, making it challenging for direct domain adaption from perspective methods. This survey reviews recent panoramic vision techniques with a particular emphasis on the perspective-to-panorama adaptation. We first revisit the panoramic imaging pipeline and projection methods to build the prior knowledge required for analyzing the structural disparities. Then, we summarize three challenges of domain adaptation: severe geometric distortions near the poles, non-uniform sampling in Equirectangular Projection (ERP), and periodic boundary continuity. Building on this, we cover 20+ representative tasks drawn from more than 300 research papers in two dimensions. On one hand, we present a cross-method analysis of representative strategies for addressing panoramic specific challenges across different tasks. On the other hand, we conduct a cross-task comparison and classify panoramic vision into four major categories: visual quality enhancement and assessment, visual understanding, multimodal understanding, and visual generation. In addition, we discuss open challenges and future directions in data, models, and applications that will drive the advancement of panoramic vision research. We hope that our work can provide new insight and forward looking perspectives to advance the development of panoramic vision technologies. Our project page is https://insta360-research-team.github.io/Survey-of-Panorama