Hello,
I am training a fully convolutional model for segmentation following the FCN paper with a VGG16 encoder. I know it is usually helpful to use pretrained weights to initialize any deep architecture but can anyone provide an intuition on why it is so crucial to have pertrained weights for the encoder of FCN? As the paper mentions, training a FCN from scratch is very hard. I am just wondering what is special about an FCN architecture that makes it so difficult to train from scratch (vs a regular classification CNN that can be trained from scratch reasonably easily)?
Thanks for your thoughts!