3 papers
VoDaSuRe: A Large-Scale Dataset Revealing Domain Shift in Volumetric Super-Resolution
August Leander Høeg, Sophia Wiinberg Bardenfleth, Hans Martin Kjer +3
Recent advances in volumetric super-resolution (SR) have demonstrated strong performance in medical and scientific imaging, with transformer- and CNN-based approaches achieving imp…
MTVNet: Mapping using Transformers for Volumes -- Network for Super-Resolution with Long-Range Interactions
August Leander Høeg, Sophia W. Bardenfleth, Hans Martin Kjer +3
Until now, it has been difficult for volumetric super-resolution to utilize the recent advances in transformer-based models seen in 2D super-resolution. The memory required for sel…
BugNIST -- a Large Volumetric Dataset for Object Detection under Domain Shift
Patrick Møller Jensen, Vedrana Andersen Dahl, Carsten Gundlach +3
Domain shift significantly influences the performance of deep learning algorithms, particularly for object detection within volumetric 3D images. Annotated training data is essenti…