  While current methods for interactive Video Object Segmentation (iVOS) rely
on scribble-based interactions to generate precise object masks, we propose a
Click-based interactive Video Object Segmentation (CiVOS) framework to simplify
the required user workload as much as possible. CiVOS builds on de-coupled
modules reflecting user interaction and mask propagation. The interaction
module converts click-based interactions into an object mask, which is then
inferred to the remaining frames by the propagation module. Additional user
interactions allow for a refinement of the object mask. The approach is
extensively evaluated on the popular interactive~DAVIS dataset, but with an
inevitable adaptation of scribble-based interactions with click-based
counterparts. We consider several strategies for generating clicks during our
evaluation to reflect various user inputs and adjust the DAVIS performance
metric to perform a hardware-independent comparison. The presented CiVOS
pipeline achieves competitive results, although requiring a lower user
workload.
