krasserm/super-resolution
TensorFlow 2 implementation of deep learning models for single image super-resolution using EDSR, WDSR, and SRGAN architectures.
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This repository provides implementations of three prominent deep learning architectures for image super-resolution: EDSR (NTIRE 2017 winner), WDSR (NTIRE 2018 winner), and SRGAN (generative adversarial approach). It includes a high-level training API, automatic DIV2K dataset downloading, and fine-tuning capabilities for combining enhancement models with SRGAN for photo-realistic results.
Frequently asked
- What is krasserm/super-resolution?
- TensorFlow 2 implementation of deep learning models for single image super-resolution using EDSR, WDSR, and SRGAN architectures.
- Is super-resolution open source?
- Yes — krasserm/super-resolution is open source, released under the Apache-2.0 license.
- What language is super-resolution written in?
- krasserm/super-resolution is primarily written in Python.
- How popular is super-resolution?
- krasserm/super-resolution has 1.5k stars on GitHub.
- Where can I find super-resolution?
- krasserm/super-resolution is on GitHub at https://github.com/krasserm/super-resolution.