What are some deep learning models that can use supplementary information other than RGB channels for image segmentation? river with indication of flow directions For example imagine a poorly shot image of a river (blue) that shows a gap, and the supplementary information are detailed flow directions (arrows) which help showing the river's true shape (no gap in reality). To get the river shape, most image segmentation models I see such as U-Net only uses RGB channels. Are there any neural network models that can use this kind of auxiliary information along with RGB channels during training for the image segmentation task?


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