Unsupervised Learning of Consensus Maximization for 3D Vision Problems

CVPR 2019 Thomas Probst Danda Pani Paudel Ajad Chhatkuli Luc Van Gool

Consensus maximization is a key strategy in 3D vision for robust geometric model estimation from measurements with outliers. Generic methods for consensus maximization, such as Random Sampling and Consensus (RANSAC), have played a tremendous role in the success of 3D vision, in spite of the ubiquity of outliers... (read more)

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