Here you find datasets, experimental as well as synthetic, for the community to better optimize algorithm settings, develop new algorithms, and for the comparison of assessed uncertainties. We welcome everyone to share meaningful datasets and refer to the relevant forum for discussions and idea.
| Sample | Name | Type | Description | Source |
|---|---|---|---|---|
 | JP-EXF01-20 | Synthetic | Datasets used in Barnkob and Rossi, Exp Fluids (2020). | link |
 | DT-WTE01-20 | Synthetic | Work-Through Example 1 (WTE1) for DefocusTracker (similar to Dataset II in BR-SYN-20). | link |
 | DT-WTE02-20 | Experimental | Work-Through Example 2 (WTE2) for DefocusTracker. | link |
 | DT-WTE03-20 | Experimental | Work-Through Example 3 (WTE3) for DefocusTracker. | link |
 | JP-MST01-21 | Synthetic | Datasets used in proposed challenge in Barnkob et al., MST (2021). For access to the full datasets, please contact the authors. | link |
Naming convention: XX-KKKNN-YY
XX: Two letters for the source type (e.g. DT: defocustracking.com, JP: journal paper).
KKK: Three letters as dataset tag (e.g. WTE: work-through-example, EXF: Experiments in Fluids).
NN: Two sequential digits (eg. 01, 02, …).
YY: Year of dataset release.
License: All datasets provided on this page are published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. This means that you must attribute the work in the manner specified by the authors, you may not use this work for commercial purposes, and if you alter, transform, or build upon this work, you may distribute the resulting work only under the same license.