These architectures have shown good results in semantic segmentation, image reconstruction (denoising, super-resolution).
I would encourage you to use SegNet if you don't see any
major performance decrease with Unet: SegNet will be lighter and faster !
SegNet uses maximum unpooling during the upsampling step, reusing the
maximum pooling indices from the encoding step. Making the upsampling
procedure parameter free, where Unet makes use of transpose convolution
(filters) to learn how to upsample.