DeepPose: Human Pose Estimation via Deep Neural Networks

TLDR

Pose estimation is formulated as a DNN‑based regression problem toward body joints. The authors propose a human pose estimation method based on deep neural networks. They use a cascade of DNN regressors to achieve high‑precision pose estimates. The method achieves state‑of‑the‑art performance on four diverse benchmarks and offers a holistic, simple yet powerful formulation that leverages recent deep learning advances.

Abstract

We propose a method for human pose estimation based on Deep Neural Networks (DNNs). The pose estimation is formulated as a DNN-based regression problem towards body joints. We present a cascade of such DNN regres- sors which results in high precision pose estimates. The approach has the advantage of reasoning about pose in a holistic fashion and has a simple but yet powerful formula- tion which capitalizes on recent advances in Deep Learn- ing. We present a detailed empirical analysis with state-of- art or better performance on four academic benchmarks of diverse real-world images.