Content-aware frame interpolation (CAFI): Deep Learning-based temporal super-resolution for fast bioimaging
Link to the paper: link
Content-aware frame interpolation (CAFI) provides a Deep Learning-based temporal super-resolution for fast bioimaging. It increases the frame rate of any microscope modality by interpolating an image in between two consecutive images via “intelligent” interpolation, providing a 2x increase in temporal or/and axial resolution. Here we provide the modified repositories of DAIN and Zooming SlowMo used in the CAFI 4 Microscopy Google Colab notebooks.
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| Demonstration Video | Tutorial Video CAFI (DAIN) | Tutorial Video CAFI (ZS) |
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DAIN 4 Microscopy:
Original Github of DAIN | Source Paper 1
ZoomingSlowMo 4 Microscopy
Original Github of ZS | Source Paper 1 | Source Paper 2
Microscopy training and test data is available here:
Martin Priessner, David C.A Gaboriau, Arlo Sheridan, Tchern Lenn, Jonathan R. Chubb, Uri Manor, Ramon Vilar, and Romain F. Laine
Content-aware frame interpolation (CAFI): Deep Learning-based temporal super-resolution for fast bioimaging. bioRxiv, 2021. DOI: https://doi.org/10.1101/2021.11.02.466664
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