BerfScene：面向无限三维场景生成的鸟瞰图条件等变辐射场
BerfScene: Bev-conditioned Equivariant Radiance Fields for Infinite 3D Scene Generation
AI总结：
BerfScene提出一种鸟瞰图条件等变辐射场表示，通过局部场景合成与平滑拼接实现大规模乃至无限规模三维场景生成，并支持通过操控鸟瞰图编辑场景物体。
摘要：
生成大规模三维场景不能简单地套用现有的三维物体合成技术，因为三维场景通常具有复杂的空间配置，并由大量尺度各异的物体组成。为此，我们提出一种实用且高效的三维表示，将等变辐射场与鸟瞰图（BEV）引导相结合。具体而言，合成三维场景中的物体可以通过操控相应的鸟瞰图来方便地进行编辑。此外，通过在生成器中充分引入位置编码和低通滤波器，该表示对给定的鸟瞰图具有等变性。这种等变性使我们能够通过合成局部场景并将其平滑一致地拼接，从而生成大规模甚至无限规模的三维场景。在三维场景数据集上的大量实验证明了我们方法的有效性。我们的项目网站为 https://zqh0253.github.io/BerfScene/。
英文摘要：
Generating large-scale 3D scenes cannot simply apply existing 3D object synthesis technique since 3D scenes usually hold complex spatial configurations and consist of a number of objects at varying scales. We thus propose a practical and efficient 3D representation that incorporates an equivariant radiance field with the guidance of a bird's-eye view (BEV) map. Concretely, objects of synthesized 3D scenes could be easily manipulated through steering the corresponding BEV maps. Moreover, by adequately incorporating positional encoding and low-pass filters into the generator, the representation becomes equivariant to the given BEV map. Such equivariance allows us to produce large-scale, even infinite-scale, 3D scenes via synthesizing local scenes and then stitching them with smooth consistency. Extensive experiments on 3D scene datasets demonstrate the effectiveness of our approach. Our project website is at https://zqh0253.github.io/BerfScene/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
