Progressive Rain Removal Based on the Combination Network of CNN and Transformer

Figure 3

The architecture of dense block. There are two 1 × 1 convolution layers in this module. The first convolution realizes the aggregation of past features, and the second convolution aggregates the aggregated past features and current features. Then, the features will be processed by a residual network.