Crowd Transformer Network

Understand

In this paper, we tackle the problem of Crowd Counting, and present a crowd density estimation based approach for obtaining the crowd count.

• Most of the existing crowd counting approaches rely on local features for estimating the crowd density map.
• In this work, we investigate the usefulness of combining local with non-local features for crowd counting.
• We use convolution layers for extracting local features, and a type of self-attention mechanism for extracting non-local features.