FACTORMATTE

While FactorMatte is designed to address videos featuring complex cross-component interactions, we find that it also excels on scenes without such interactions. One example would be the task of classical video matting... Our method is trained per-video and requires neither pre-training on external large datasets, nor knowledge about the 3D structure of the scene. We conduct extensive experiments, and show that our method not only can disentangle scenes with complex interactions, but also outperforms top methods on existing tasks such as classical video matting and background subtraction. In addition, we demonstrate the benefits of our approach on a range of downstream tasks.