Semantic segmentation is a far trickier task for video than for static images, either resulting in temporally inconsistent – or costly and inaccurate – predictions. This is where Momentum Adapt can help. Where most approaches attempt to solve temporal inconsistency issues by using optical flow networks or altering the architecture of the network, momentum adapt uses two semantic segmentation networks with identical architecture and tries to increase the model’s confidence by taking their predict