We present Genie Sim PanoRecon, a feed-forward Gaussian-splatting pipeline that delivers high-fidelity, low-cost 3D scenes for robotic manipulation simulation. The panorama input is decomposed into six non-overlapping cube-map faces, processed in parallel, and seamlessly reassembled. To guarantee geometric consistency across views, we devise a depth-aware fusion strategy coupled with a training-free depth-injection module that steers the monocular feed-forward network to generate coherent 3D Gaussians. The whole system reconstructs photo-realistic scenes in seconds and has been integrated into Genie Sim - a LLM-driven simulation platform for embodied synthetic data generation and evaluation - to provide scalable backgrounds for manipulation tasks. For code details, please refer to: https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_world.

翻译：我们提出Genie Sim PanoRecon——一种前馈式高斯泼溅流水线，能够为机器人操作仿真生成高保真、低成本的3D场景。我们将全景输入分解为六个无重叠的立方体贴图面，并行处理后无缝重组。为保证跨视角的几何一致性，我们设计了一种深度感知融合策略，并配备无需训练的深度注入模块，引导单目前馈网络生成连贯的3D高斯体。整个系统可在数秒内重建逼真场景，并已集成至Genie Sim——一个面向具身合成数据生成与评估的大语言模型驱动仿真平台——为操作任务提供可扩展的背景环境。代码详情请参见：https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_world。