Digital Volume Correlation Challenge 2.0: A Comprehensive Dataset for Digital Volume Correlation Benchmarking

DVC Challenge 2.0 compiles a diverse collection of volumetric images contributed by the global research community specifically for use with Digital Volume Correlation (DVC) codes. These datasets encompass different materials, loading conditions, and imaging modalities. It includes confocal/multiphoton microscopy, X-ray computed tomography (XCT), neutron tomography (NCT), and synthetically generated images. These datasets present various challenges, such as complex deformation fields, poor image quality, and anisotropic or sparse speckle patterns to challenge DVC codes. All datasets are compiled into a data framework with a uniform format and made openly accessible. This repository provides benchmark data for validating and comparing DVC algorithms, facilitating the exploration of DVC capabilities in diverse and challenging scenarios. The repository consists of 37 datasets from 19 participants affiliated with 17 organizations. For more details see the "README" and "data_summary" files. For a visual overview of the organization of the datasets look at the "folder_structure_summary" file. A manuscript describing the datasets with baseline DVC performance provides further details.