Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report

@article{Ignatov2021FastCI,
  title={Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report},
  author={Andrey D. Ignatov and Kim Byeoung-su and R. Timofte and Angeline Pouget and Fenglong Song and Cheng Li and Shuai Xiao and Zhongqian Fu and Matteo Maggioni and Yibin Huang and Shen Cheng and Xin Lu and Yifeng Zhou and Liangyu Chen and Donghao Liu and Xiangyu Zhang and Haoqiang Fan and Jian Sun and Shuaicheng Liu and Minsu Kwon and Myungje Lee and Jaeyoon Yoo and Changbeom Kang and Shinjo Wang and Bin Huang and Tianbao Zhou and Shuai Liu and Lei Lei and Chaoyu Feng and Liguang Huang and Z. Lei and Feifei Chen},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2021},
  pages={2515-2524}
}
  • Andrey D. Ignatov, Kim Byeoung-su, +29 authors Feifei Chen
  • Published 2021
  • Computer Science, Engineering
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data and are too computationally expensive to run on mobile devices. To address this problem, we introduce the first Mobile AI challenge, where the target is to develop an end-to-end deep learning-based image denoising solution that can demonstrate high efficiency on smartphone GPUs. For this, the participants were… Expand

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Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Report
  • Andrey D. Ignatov, R. Timofte, +20 authors Shengpeng Wang
  • Computer Science, Engineering
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • 2021
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The first Mobile AI challenge is introduced, where the target is to develop an end-to-end deep learning-based image super-resolution solutions that can demonstrate a real-time performance on mobile or edge NPUs. Expand
Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report
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The target is to develop an end-to-end deep learning-based video super-resolution solutions that can achieve a realtime performance on mobile GPUs and can upscale videos to HD resolution at up to 80 FPS while demonstrating high fidelity results. Expand
Learned Smartphone ISP on Mobile NPUs with Deep Learning, Mobile AI 2021 Challenge: Report
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