Review: G-RMI — 1st Runner Up in COCO KeyPoint Detection Challenge 2016 (Human Pose Estimation)

Original article can be found here (source): Artificial Intelligence on Medium

Review: G-RMI — 1st Runner Up in COCO KeyPoint Detection Challenge 2016 (Human Pose Estimation)

Two-Stage Top-Down Approach: First, Person Detection. Then, Keypoint Detection.

Two-stage Approach

In this story, G-RMI for person keypoint detection or human pose estimation, by Google Inc., is reviewed. G-RMI, Google Research, and Machine Intelligence should be the team name rather than the approach name.

To detect a multi-person and estimate the pose, a two-stage approach is proposed.

  • First, multi-person are detected using Faster R-CNN.
  • Then, fully convolutional ResNet is used to detect the keypoint of each person.

This is the 2017 CVPR paper with over 200 citations. (Sik-Ho Tsang @ Medium)