  We present VSAC, a RANSAC-type robust estimator with a number of novelties.
It benefits from the introduction of the concept of independent inliers that
improves 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 is
run on average only once. Further technical improvements include adaptive
sequential hypothesis verification and efficient model estimation via Gaussian
elimination. Experiments on four standard datasets show that VSAC is
significantly 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 repeated
runs on EVD, HPatches, PhotoTourism, and Kusvod2 datasets, it never failed.
