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Novel view synthesis of static scenes has achieved remarkable advancements inproducing photo-realistic results. However, key challenges remain for immersiverendering of dynamic scenes. One of the seminal image-based rendering method,the multi-plane image (MPI), produces high novel-view synthesis quality forstatic scenes. But modelling dynamic contents by MPI is not studied. In thispaper, we propose a novel Temporal-MPI representation which is able to encodethe rich 3D and dynamic variation information throughout the entire video ascompact temporal basis and coefficients jointly learned. Time-instance MPI forrendering can be generated efficiently using mini-seconds by linearcombinations of temporal basis and coefficients from Temporal-MPI. Thusnovel-views at arbitrary time-instance will be able to be rendered viaTemporal-MPI in real-time with high visual quality. Our method is trained andevaluated on Nvidia Dynamic Scene Dataset. We show that our proposed Temporal-MPI is much faster and more compact compared with other state-of-the-artdynamic scene modelling methods.

Temporal-MPI: Enabling Multi-Plane Images for Dynamic Scene Modelling via Temporal Basis Learning