# Pantheon360：利用3D感知360°视频扩散来驾驭数字孪生生成

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-05-25 08:00
- AIHOT 分数：68
- AIHOT 链接：https://aihot.virxact.com/items/cmpm0ai190kf8sl011knf7lnn
- 原文链接：https://arxiv.org/abs/2605.25449

## AI 摘要

Pantheon360是一个可控的360°视频生成框架，旨在从稀疏的360°输入合成高保真视频，以解决传统透视视频生成器因视野有限而导致的轨迹复杂、跨视角不一致等问题。其核心创新是引入一个从输入中重建的显式3D缓存，作为用户定义任意相机路径的几何支架。这使视频扩散模型能专注于纹理精修，同时由3D缓存强制执行全局几何一致性。实验表明，该框架在视觉质量和几何一致性上表现优越，能够为下游模拟和数字孪生应用提供可靠、灵活的360°场景生成。

## 正文

Generating complete digital twins from videos requires precise camera control, global scene coverage, and strict spatial-temporal consistency constraints that remain challenging for perspective video generators due to their limited field of view (FoV). Their narrow FoV forces long or multi-view trajectories, amplifying cross-view inconsistency and temporal drift. We argue that 360° video generation offers a natural solution: panoramic coverage simplifies trajectory design and provides a strong global context for maintaining coherence. We introduce Pantheon360: Taming Digital Twin Generation via 3D-Aware 360° Video Diffusion, a controllable 360° video generation framework that synthesizes high-fidelity videos from sparse 360° inputs. The key idea is an explicit 3D Cache, reconstructed from the input, which serves as a geometric scaffold for any user-defined camera path. This allows the diffusion model to focus on photorealistic texture refinement while the 3D Cache enforces global geometric consistency. Experiments show that Pantheon360 achieves superior visual quality and unmatched geometric coherence, enabling reliable and flexible 360° scene generation for downstream simulation and digital-twin applications.