  Multi-Person Pose Estimation is an interesting yet challenging task in
computer vision. In this paper, we conduct a series of refinements with the
MSPN and PoseFix Networks, and empirically evaluate their impact on the final
model performance through ablation studies. By taking all the refinements, we
achieve 78.7 on the COCO test-dev dataset and 76.3 on the COCO test-challenge
dataset.
