Sep 1, 2012 · We utilize the unlabeled data to compensate for the complexities in the input space and model the underlying manifold by a nearest neighbor ...
Sep 1, 2012 · Graph based semi-supervised human pose estimation: When the output space comes to help. Author links open overlay panel. Nima Pourdamghani
Graph based semi-supervised human pose estimation: When the output space comes to help ... space and model the underlying manifold by a nearest neighbor graph.
5 days ago · 1 Introduction. In the research on 3D human pose estimation from 2D pose estimation in videos, emphasis is placed on comprehending human posture ...
distances of points in the input space, corresponding to their distances in the output space. The proposed label estimation method works based on the ...
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Faghri, M. H. Rohban, “Graph Based Semi-Supervised Human Pose Estimation : When The Output Space Comes to Help,” Pattern Recognition Letters, vol. 33, p.p ...
Graph based semi-supervised human pose estimation: When the output space comes to help. , Article Pattern Recognition Letters ; Volume 33, Issue 12 ...
In this paper, we use the distances between the labels of the training data to learn a metric and map the input data to a space where this problem is minimized.
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6 days ago · The challenge of estimating 3D pose has been thoroughly explored and researched in computer vision due to its broad range of applications.
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Consistency-based methods enforce model outputs to be consistent when its input is randomly perturbed. ... Semi-supervised learning with contrastive graph ...