Data provided by National Institute of Standards and Technology
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.
For ease of use with the Public Data Repository individual datasets have been combined in .zip containers. The complete dataset consists of 51 files and 189 GB of data.
About this Dataset
Updated: 2026-09-04
Metadata Last Updated:
2026-03-09 00:00:00
Date Created:
N/A
Data Provided by:
Dataset Owner:
N/A
| Title | Digital Volume Correlation Challenge 2.0: A Comprehensive Dataset for Digital Volume Correlation Benchmarking |
|---|---|
| Description | 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. For ease of use with the Public Data Repository individual datasets have been combined in .zip containers. The complete dataset consists of 51 files and 189 GB of data. |
| Modified | 2026-03-09 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Digital Volume Correlation , Benchmark dataset , Micro-X-ray computed tomography , Confocal microscopy , Synthetic image generation , Neutron imaging , Optical coherence tomography , Uncertainty quantification |
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"publisher": {
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"name": "National Institute of Standards and Technology"
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"Materials:Composites",
"Materials:Modeling and computational material science",
"Materials:Polymers",
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"Benchmark dataset",
"Micro-X-ray computed tomography",
"Confocal microscopy",
"Synthetic image generation",
"Neutron imaging",
"Optical coherence tomography",
"Uncertainty quantification"
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}
