Design of A Backbone without Pretraining

The excellent performance of deep learning depends on the strong representation ability of its backbone. As a conventional means of most backbones, pretraining can make the model obtain high accuracy, but it also brings some disadvantages that can not be ignored: first, the structures of the backbones need pretraining are fixed, they are difficult to modify and migrate across tasks; second, the pr...