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We start from a high-resolution subnetwork as the first stage, gradually add high-to-low resolution subnetworks one by one to form more stages, and connect the mutli-resolution subnetworks in parallel.
#2 best model for Pose Estimation on COCO (using extra training data)
This paper addresses the problem of estimating and tracking human body keypoints in complex, multi-person video.
#5 best model for Pose Tracking on PoseTrack2017 (using extra training data)
To the best of our knowledge, this is the first paper to propose an online human pose tracking framework in a top-down fashion.
#2 best model for Pose Tracking on PoseTrack2017 (using extra training data)
We introduce multigrid Predictive Filter Flow (mgPFF), a framework for unsupervised learning on videos.
The current state-of-the-art approaches have yet to gain from the dramatic increase in performance reported in human pose tracking and 2D facial landmark placement due to the use of deep convolutional neural networks (CNN).