Dataset - Deep Recurrent Optical Flow Learning for Particle Image Velocimetry Data
- 1. RWTH Aachen University
- 2. German Center for Neurodegenerative Diseases (DZNE)
Description
This is the official dataset of Recurrent All-Pairs Field Transforms for Particle Image Velocimetry Data (RAFT-PIV) published in Nature Machine Intelligence. In this work, we propose a deep neural network-based approach for learning displacement fields in an end-to-end manner, focusing on the specific case of Particle Image Velocimetry (PIV).
PIV is a key approach in experimental fluid dynamics and of fundamental importance in diverse applications, including automotive, aerospace, and biomedical engineering. In contrast to standard PIV methods, our RAFT-PIV approach is general, largely automated, and provides much higher spatial resolution. This dataset is given as binary TFRECORD format.
Files
Data_ProblemClass2_RAFT-PIV.zip
Files
(12.2 GB)
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