2017

Towards Accurate Multi-person Pose Estimation in the Wild

Papandreou, George, Zhu, Tyler, Kanazawa, Nori et al.

Understand

We propose a method for multi-person detection and 2-D pose estimation that achieves state-of-art results on the challenging COCO keypoints task.

It is a simple, yet powerful, top-down approach consisting of two stages.
In the first stage, we predict the location and scale of boxes which are likely to contain people; for this we use the Faster RCNN detector.
In the second stage, we estimate the keypoints of the person potentially contained in each proposed bounding box.

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