I haven't understand your network. about implicit-internal-video-inpainting

[mgwillia]

Hi, I am not one of the authors of this paper, but it seems you misunderstand the ideas that motivate implicit representation, and in particular, implicit representation for video inpainting.

Long story short, this is a zero-shot task. There is no "training" and "testing" in the traditional ML sense. The model receives as inputs the frames and some masks (as few as one mask!) for inpainting. It iterates on those frames, learning how to inpaint for that specific video, until convergence, which is when it delivers a satisfactory inpainting. It doesn't need general visual priors from expensive pretraining- this is not desirable. As an implicit method, the visual priors the network learns from the video of interest are sufficient.