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Research map / Learning theory and algorithms / Prediction and decision losses

Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach

CVPR 2021 · Learning theory and algorithms › Prediction and decision losses · approach: Distributionally robust optimization · 11 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the proposed unsupervised RL method instead of RANSAC or LO-RANSAC2D line fitting · Synthetic 2D line fittingconsensus sizeHelped
Use the proposed unsupervised RL method instead of A*2D line fitting · Synthetic 2D line fittingruntimeHelped
Use the proposed unsupervised RL method instead of random action selection3D plane fitting · Synthetic 3D plane fittingsolution qualityHelped
Use the proposed unsupervised RL method instead of A* methods3D plane fitting · Synthetic 3D plane fittingruntimeHelped
Use the proposed unsupervised RL method instead of RANSAC-based methodsFundamental matrix estimation · ModelNet40consensus sizeHelped
Use the proposed unsupervised RL method instead of ULCMFundamental matrix estimation · ModelNet40consensus sizeHelped
Use the proposed unsupervised RL method instead of ULCMFundamental matrix estimation · KITTIconsensus sizeHelped
Use the proposed unsupervised RL method instead of RANSACFundamental matrix estimation · KITTImedian consensus sizeHelped
Test with twice as many points and higher outlier rates without retrainingProposed method · Synthetic 2D line fittingsolution qualityNo clear effect
Test with twice as many points and higher outlier rates without retrainingProposed method · Synthetic 3D plane fittingsolution qualityNo clear effect

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