SinGRAV: Learning a Generative Radiance Volume from a Single Natural Scene

Understand

We present a 3D generative model for general natural scenes.

• Lacking necessary volumes of 3D data characterizing the target scene, we propose to learn from a single scene.
• Our key insight is that a natural scene often contains multiple constituents whose geometry, texture, and spatial arrangements follow some clear patterns, but still exhibit rich variations over different regions within the same scene.
• This suggests localizing the learning of a generative model on substantial local regions.