Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels

NeurIPS 2019 Natalia NeverovaDavid NovotnyAndrea Vedaldi

Many machine learning methods depend on human supervision to achieve optimal performance. However, in tasks such as DensePose, where the goal is to establish dense visual correspondences between images, the quality of manual annotations is intrinsically limited... (read more)

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