  Partial occlusion effects are a phenomenon that blurry objects near a camera
are semi-transparent, resulting in partial appearance of occluded background.
However, it is challenging for existing bokeh rendering methods to simulate
realistic partial occlusion effects due to the missing information of the
occluded area in an all-in-focus image. Inspired by the learnable 3D scene
representation, Multiplane Image (MPI), we attempt to address the partial
occlusion by introducing a novel MPI-based high-resolution bokeh rendering
framework, termed MPIB. To this end, we first present an analysis on how to
apply the MPI representation to bokeh rendering. Based on this analysis, we
propose an MPI representation module combined with a background inpainting
module to implement high-resolution scene representation. This representation
can then be reused to render various bokeh effects according to the controlling
parameters. To train and test our model, we also design a ray-tracing-based
bokeh generator for data generation. Extensive experiments on synthesized and
real-world images validate the effectiveness and flexibility of this framework.
