Weakly-supervised Video Polyp Segmentation by Voting

Weakly-supervised video polyp segmentation is challenging because of no accurate ground truths. This paper proposes a scribble based framework called Voting based Video Polyp Segmentation (VotingVPS), which is based on the statistical advantage of voting in choosing the optimal candidates. For the robust pseudo masks, voting is integrated into the visual foundation model SAM to obtain effective supervision. Considering the initial prediction is also important for the refinement, the framework also designs a morphology based encoder-decoder module for this purpose. Experimental results show the effectiveness of the framework for weakly-supervised video polyp segmentation.