Mysterious EfficientNets

The research paper Rethinking Model Scaling for Convolutional Neural Networks introduces a family of EfficientNet architecture. In the paper, they systematically study model scaling and identify that carefully balancing network depth, width and resolution can lead to better results. The paper introduces a compound scaling method that uniformly scales all dimensions of depth, width and resolution. I feel that it has covered a missing piece in designing CNN architectures. The paper states that the key idea is to balance all dimensions and it can be achieved by scaling each of them with constant ratio.