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Erroneous feature matches have severe impact on subsequent camera pose estimation and often require additional, time-costly measures, like RANSAC, for outlier rejection.
Concerning nonnegative matrices and doubly stochastic matrices
Richard Sinkhorn and Paul Knopp · 1967
Earlier work this paper cites.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A. Fischler and Robert C. Bolles · 1981
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A computer algorithm for reconstructing a scene from two projections
Hugh Christopher Longuet-Higgins · 1981
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R.I. Hartley · 1997
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Matrix backpropagation for deep networks with structured layers
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Adam: A method for stochastic optimization
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Eric Brachmann and Carsten Rother · 2019
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Mihai Dusmanu, Ignacio Rocco, Tomás Pajdla, Marc Pollefeys, Josef Sivic, Akihiko Torii, and Torsten Sattler · 2019
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Learning two-view correspondences and geometry using order-aware network
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