Many of the architectures that do semantic segmentation like SegNet, DilatedNet (Yu and Koltun), DeepLab, etc. do not work on high resolution images. For such benchmarks like Cityscapes, what is a standard/practical approach for such methods to perform on the benchmark?
I've tried to look into the paper, but I couldn't find such details. There's an article mentioning that they output at 1/8 of input images than do interpolation (usually 2, 4 or 8 times) from their results, but the article does not specify which upsampling techniques are the most reasonable one.