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title: Image Denoising Demo | |
emoji: π | |
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} | |
} | |