SOURCE-LINKED INTELLIGENCE

RAFT-DVC: Resolution-Aware Machine Learning-Based Digital Volume Correlation

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Digital volume correlation (DVC) provides three-dimensional full-field displacement measurements from volumetric images, but how the internal resolution of a machine-learning-based DVC model affects accuracy and operating range remains poorly understood. Here, we present RAFT-DVC, a resolution-aware family of recurrent all-pairs field transforms (RAFT)-based DVC solvers with encoder downsampling factors s = 2, 4, and 8. Using a matched design, we find that the three solvers localize displacement to approximately 0.017 feature-grid voxel, giving an empirical raw-volume error scaling of approxim

Read original source ↗ Open in workspace

recordType

paper

region

Global