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We present VSAC, a RANSAC-type robust estimator with a number of novelties.It benefits from the introduction of the concept of independent inliers thatimproves significantly the efficacy of the dominant plane handling and, also,allows near error-free rejection of incorrect models, without false positives.The local optimization process and its application is improved so that it isrun on average only once. Further technical improvements include adaptivesequential hypothesis verification and efficient model estimation via Gaussianelimination. Experiments on four standard datasets show that VSAC issignificantly faster than all its predecessors and runs on average in 1-2 ms,on a CPU. It is two orders of magnitude faster and yet as precise as MAGSAC++,the currently most accurate estimator of two-view geometry. In the repeatedruns on EVD, HPatches, PhotoTourism, and Kusvod2 datasets, it never failed.

VSAC: Efficient and Accurate Estimator for H and F