jiangsutx/SRN-Deblur
A deep neural network for removing blur from images using a scale-recurrent architecture.
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This repository implements the SRN-Deblur model from CVPR 2018, a deep learning approach to image deblurring. The network uses scale-recurrent mechanisms to progressively restore sharp images from blurry inputs across multiple resolution scales. Built with TensorFlow 1.4, it requires GPU for efficient processing and accepts blurry images to output deblurred results.
Frequently asked
- What is jiangsutx/SRN-Deblur?
- A deep neural network for removing blur from images using a scale-recurrent architecture.
- Is SRN-Deblur open source?
- Yes — jiangsutx/SRN-Deblur is open source, released under the MIT license.
- What language is SRN-Deblur written in?
- jiangsutx/SRN-Deblur is primarily written in Python.
- How popular is SRN-Deblur?
- jiangsutx/SRN-Deblur has 763 stars on GitHub.
- Where can I find SRN-Deblur?
- jiangsutx/SRN-Deblur is on GitHub at https://github.com/jiangsutx/SRN-Deblur.