# pytorch\-image\-super\-resolution

[DecompHub listing](<https://app.decomphub.com/projects/pytorch-image-super-resolution>) · [JSON record](<https://app.decomphub.com/data/projects/pytorch-image-super-resolution.json>)

## Description

> PyTorch reimplementation of SRCNN and SRGAN for single\-image super\-resolution on the DIV2K dataset\. Features a modular codebase with shared components for fair comparison between CNN\- and GAN\-based methods\. Includes training, evaluation, and reproducibility support to validate results against the original papers\.

- Category: applications
- Work types: reimplementation
- Targets: Unknown
- Project status: unknown
- Listing updated: 2026\-10\-09T04:57:21\.197Z
- Listing first published: 2026\-10\-09T04:57:21\.198Z

## Repository

- Repository: [easontan03/pytorch\-image\-super\-resolution](<https://github.com/easontan03/pytorch-image-super-resolution>)
- License: Not specified
- Repository stars: 0
- Stars checked: 2026\-10\-09T04:48:52\.441Z
- Repository metadata checked: 2026\-10\-09T04:48:52\.441Z

## Progress

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No sourced numeric progress is currently reported. This is unknown progress, not 0%.

## Project details

- Languages: Jupyter Notebook

## Contributing

- Contribution status: unknown
- Help requested: Not reported
- Contribution instructions: Not reported
- Contribution source: Not reported
- Contribution information checked: Not reported
- AI contribution policy: unspecified
- AI policy source: Not reported

## Listing sources

- [Public repository metadata](<https://github.com/easontan03/pytorch-image-super-resolution>)
- [Discovery query](<https://api.github.com/search/repositories?q=%22reimplementation%22+in%3Aname%2Cdescription+is%3Apublic+fork%3Afalse+created%3A2025-03-22..2025-10-24&sort=updated&order=desc&per_page=100&page=6>)

## Data notes

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