Graph based semi-supervised human pose estimation: When the output space comes to help

Linear discriminant analysis (LDA) is a well-known dimensionality reduction method which can be easily extended for data classification. Traditional LDA aims to preserve the separability of different classes and the compactness of the same class in the ...

• Human pose estimation is achieved by semi- and weakly-supervised learning.
• Semi-...

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For human pose estimation in still images, this paper proposes three semi- and weakly-supervised learning schemes. While recent advances of convolutional neural networks improve human pose estimation using supervised training data, our ...

Graph Laplacian manifold regularization exploits the intrinsic geometrical properties of the underlying graph over both labeled and unlabeled data to approximate an optimal smooth prediction function. The regularization works on the ...

• Dropout limits participation of unlabeled nodes to solve the problem of function degeneration.