Deep social grouping network for large scenes with multiple subjects

Abstract

In computer vision, more attention has been paid to group analysis, and the group detection in images becomes a key technology of human analysis on groups. The existing social grouping methods only focus on small scenes with fixed number of persons and cannot deal with large scene images in the real world. This paper proposes the first fine-grained social grouping framework for gigapixel large scene images based on deep learning, which consists of a graph-guided global-to-local partition strategy and a deep grouping network that learns an implicit respresentation for social pairs. The framework has achieved accurate grouping on large scene images. Our method is also applicable to small scene images, and has outperformed the existing methods. The relevant code and the training dataset will be released soon.