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Cross-View Variance Correlation in Path-Traced Stereo: A Hidden Shortcut in Synthetic Training Data
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Abstract
Path-traced synthetic stereo data reveal a previously unrecognized property: while the Monte Carlo noise streams between left and right cameras are independent, their variance fields show high correlation once aligned by ground-truth disparity. Across 20 Mitsuba 3 scenes, warped Pearson correlation reaches ρ = 0.754 ± 0.016 and remains invariant over a 16× sampling range. The effect is strongest in Lambertian regions and weaker in glass, which together constitute a learnable shortcut for stereo networks and a sim-to-real gap mechanism that is unique to rendered data and absent in real binocular sensors.
Keywords
- path tracing
- Monte Carlo rendering
- stereo matching
- variance correlation
- sim-to-real gap
- learnable shortcut
- Mitsuba 3
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@misc{lin2026crossview,
title = {Cross-View Variance Correlation in Path-Traced Stereo: A Hidden Shortcut in Synthetic Training Data},
author = {Po-Ting Lin},
year = {2026},
howpublished = {Zenodo},
doi = {10.5281/zenodo.19892861}
}