Identifying players in broadcast videos using graph convolutional network

Highlights：

• A novel person representation method using graph convolutional network at the level of relational induction bias is presented.

• We innovatively embed implicit pose structure information into the deep features to form high-level features.

• To the best of our knowledge, the proposed method is the first work utilizing graph convolutional network for player identification.

• Extensive experiments on real-world game scenarios show that the proposed method captures a better person representation and achieves state-of-the-art performance.