作者：L Yariv, P Hedman, C Reiser, D Verbin, P P. Srinivasan, R Szeliski, J T. Barron, B Mildenhall
[Google Research]

要点:

  1. 提出了一种新方法 BakedSDF，用于重建大型无界真实世界场景的高质量网格，以进行实时视图合成；
  2. 用混合神经体-表面场景表示法，为准确的表面重建进行了优化，然后 bake 成具有与视图相关的外观模型的三角形网格；
  3. BakedSDF 在精度、速度和功耗方面优于之前的实时渲染场景表示，可产生高质量的网格，使下游应用如外观编辑和物理模拟成为可能；
  4. 该系统可以在消费级设备上以实时帧率进行渲染，产生的网格准确而详细，可以实现标准的图形应用。

总结:
BakedSDF 是一种重建大型无界真实世界场景高质量网格的方法，适用于逼真新视图合成，在精度、速度和功耗方面优于之前的实时渲染的场景表示，可产生高质量的网格，使下游应用成为可能。

https://arxiv.org/abs/2302.14859

We present a method for reconstructing high-quality meshes of large unbounded real-world scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural volume-surface scene representation designed to have well-behaved level sets that correspond to surfaces in the scene. We then bake this representation into a high-quality triangle mesh, which we equip with a simple and fast view-dependent appearance model based on spherical Gaussians. Finally, we optimize this baked representation to best reproduce the captured viewpoints, resulting in a model that can leverage accelerated polygon rasterization pipelines for real-time view synthesis on commodity hardware. Our approach outperforms previous scene representations for real-time rendering in terms of accuracy, speed, and power consumption, and produces high quality meshes that enable applications such as appearance editing and physical simulation.

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