The natural next step in the progression from coarse to fine inference is to make a prediction at every pixel.

In-network upsampling layers enable pixelwise prediction and learning in nets with subsampled pooling.

Semantic segmentation faces an inherent tension between semantics and location: global information resolves what while local information resolves where.