Great question — answering as the UphillTech team:
I will try to do it part by part : We employ the residual network, which is trained on ImageNet dataset for image classication task, to extract the deep features to represent the density of the crowd. If you look at the figure 2, you can see that they use the Neural network architecture ResNet. This is a deep network, here is the paper. It has good performance and do image classification. This pre-trained CNN network created a residual item for every three convolution layer to bring the layer of the network to 152 If you are in the layer k, it means this layer has in input, the ouput of the k-3th layer. See the paper, figure 5 explains it well without much explications needed. Furthermore,...
Full answer by Jérémy Blain: https://ai.stackexchange.com/a/7918 (CC BY-SA 4.0).
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