Low-res two-view benchmark
This table lists the benchmark results for the low-res two-view scenario. This benchmark evaluates the Middlebury stereo metrics (for all metrics, smaller is better):
- bad 0.5, 1.0, 2.0, 4.0 [%]: Fraction of pixels with errors larger than the given number of disparities.
- Average error [px]: The per-pixel average disparity error.
- Root mean square error [px]: The per-pixel root mean square disparity error.
- 50%, 90%, 95%, 99% error quantile [px]: The highest disparity error within the given percentage of best pixels (for 50%, this is the median error).
- Time [s]: The runtime of the method.
The mask determines whether the metric is evaluated for all pixels with ground truth, or only for pixels which are visible in both images (non-occluded).
The coverage selector allows to limit the table to results for all pixels (dense), or a given minimum fraction of pixels.
Methods with suffix _ROB may participate in the Robust Vision Challenge.
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