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