Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels

Natalia Neverova, David Novotny, Andrea Vedaldi

Neural Information Processing Systems 

Analternativeapproach isto predict instead adistributionp(ˆy|x) = Φˆy(x) over possible values of the annotationy. Theannotators are shown a set of points sampled randomly and uniformly over one of predefined body parts of aperson inan image.

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