Published January 11, 2021 | Version v1
Dataset Open

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

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