text: Title: Semantic Segmentation FCN Training
  Body: I have a few issues/questions regarding training FCN using gluoncv:
  - The training script defines crop_size & base_size, but it's not documented what these are.
     So what do these mean?
  - crop_size & base_size accept a single integer value, but for inference we would potentially want to use an asymmetrical size, such as 2048x1024 (cityscapes) or 1920x1080 (full hd camera). Is there a way around this?
  - Looking at fcn.py, I don't see a way to combine the heads as in [the original paper](https://arxiv.org/abs/1411.4038)
  The paper uses upsampling (either bilinear or deconvolution) and then element-wise add in order to combine the heads.
  ![image](https://user-images.githubusercontent.com/57857737/81494687-82d4b200-92b3-11ea-9552-8c8ae2350808.png)
  It also distinguishes FCN-32, FCN-16 & FCN-8, depending on the heads.
  Did I misunderstand the code?