DyLiN: Making Light Field Networks Dynamic

Understand

Light Field Networks, the re-formulations of radiance fields to oriented rays, are magnitudes faster than their coordinate network counterparts, and provide higher fidelity with respect to representing 3D structures from 2D observations.

• They would be well suited for generic scene representation and manipulation, but suffer from one problem: they are limited to holistic and static scenes.
• In this paper, we propose the Dynamic Light Field Network (DyLiN) method that can handle non-rigid deformations, including topological changes.
• We learn a deformation field from input rays to canonical rays, and lift them into a higher dimensional space to handle discontinuities.