Factorized Motion Fields for Fast Sparse Input Dynamic View Synthesis

Understand

Designing a 3D representation of a dynamic scene for fast optimization and rendering is a challenging task.

• While recent explicit representations enable fast learning and rendering of dynamic radiance fields, they require a dense set of input viewpoints.
• In this work, we focus on learning a fast representation for dynamic radiance fields with sparse input viewpoints.
• However, the optimization with sparse input is under-constrained and necessitates the use of motion priors to constrain the learning.