Replicating 2D images into a 3D volume and processing with a shallow 3D U-Net gives competitive dense prediction accuracy at a fraction of the parameter count, with slice-consistency used as a free quality score.
U-net: Convolutional networks for biomedical image segmentation,
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Spatial Lifting for Dense Prediction
Replicating 2D images into a 3D volume and processing with a shallow 3D U-Net gives competitive dense prediction accuracy at a fraction of the parameter count, with slice-consistency used as a free quality score.