2018

Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation

Shah, Sohil, Ghosh, Pallabi, Davis, Larry S et al.

Understand

Many imaging tasks require global information about all pixels in an image.

Conventional bottom-up classification networks globalize information by decreasing resolution; features are pooled and downsampled into a single output.
But for semantic segmentation and object detection tasks, a network must provide higher-resolution pixel-level outputs.
To globalize information while preserving resolution, many researchers propose the inclusion of sophisticated auxiliary blocks, but these come at the cost of a considerable increase in network size and computational cost.

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