Fillerbuster: Unified Generative Scene Completion Model for Casual Captures

Understand

We present Fillerbuster, a unified model that completes unknown regions of a 3D scene with a multi-view latent diffusion transformer.

• Casual captures are often sparse and miss surrounding content behind objects or above the scene.
• Existing methods are not suitable for this challenge as they focus on making known pixels look good with sparse-view priors, or on creating missing sides of objects from just one or two photos.
• In reality, we often have hundreds of input frames and want to complete areas that are missing and unobserved from the input frames.