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

Figure 2

The architecture of CNCT. The input image will go through two stages: Net-C and Net-T. Net-C is a convolutional neural network, which first maps the image into depth features by shallow feature extraction module, and then continues processing by a succession of Net-C units. Net-T adopts the Transformer structure, which takes the output of the last Net-C unit as the input and processes it by a succession of Net-T units. There is a cross-stage feature fusion mechanism (pink arrows) between the corresponding units in different stages. Finally, image reconstruction module restores the depth features to images.