DeepPose: Human Pose Estimation via Deep Neural Networks
This addresses pose estimation for computer vision applications, but it is incremental as it builds on existing DNN advances.
The authors tackled human pose estimation by formulating it as a regression problem using Deep Neural Networks (DNNs) and achieved state-of-the-art or better performance on four academic benchmarks.
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 regressors 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 formulation which capitalizes on recent advances in Deep Learning. We present a detailed empirical analysis with state-of-art or better performance on four academic benchmarks of diverse real-world images.