Unlike the paper where a 49x49 AveragePooling layer with variable strides is used, our implementation uses an AdaptiveAvgPool2d layer to process the global features. This is because the authors of the paper tailored the head to the Cityscapes dataset while our focus is to provide a general purpose implementation that can work on multiple datasets. Finally our implementation always has a bilinear interpolation before returning the output to ensure that the sizes of the input and output images match exactly.
DeepLabV3 & FCN