We welcome contributions of the following:
- Retinal Vessel videos with descriptions and ground truth.
- Published benchmarking results of algorithms applied to the RVD dataset.
- Corrections to existing descriptions or ground truth.
- Other aspects of the RVD.
Contributing RVD dataset
If you would like to contribute the dataset, please email uq.cvlab@gmail.com with the following:
- a .zip file of your videos and annotations.
- 1-5 example videos.
- any metadata or ground truth data you may have (.csv, .txt files).
Please email uq.cvlab@gmail.com if you have any questions about contributing datasets.