README.md

metadata

title: Image Denoising Demo
emoji: 🏃
colorFrom: red
colorTo: gray
sdk: streamlit
sdk_version: 1.19.0
app_file: app.py
pinned: false
license: cc-by-sa-4.0

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

The method "Dense Residual Swin Transformer for Image Denoising" is included in the benchmark report "NTIRE 2023 Challenge on Image Denoising: Methods and Results" in CVPR workshop 2023.

The team include following members:

• Sunder Ali Khowaja (Department of Telecommunication Engineering, University of Sindh, Pakistan)
• Jiseok Yoon (IKLAB Inc.)
• Ik Hyun Lee (IKLAB Inc. and Tech University of Korea, Republic of Korea)

If you find the demo useful or want to use the results in your research work, kindly cite our work

@inproceedings{li2023ntire_dn50, title={NTIRE 2023 Challenge on Image Denoising: Methods and Results}, author={Li, Yawei and Zhang, Yulun and Van Gool, Luc and Timofte, Radu and others}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops}, year={2023} }