源代码见:https://github.com/cszn/SCUNet,在线去噪网址见:https://replicate.com/cszn/scunet。 全文导读 Luc Van Gool团队 | 通过Swin-Conv-UNet和数据合成实现实用图像盲去噪 全文下载: Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis https://link.springer.com/article/10.1007/s11...
the new network architecture design achieves state-of-the-art performance and the new degradation model can help to significantly improve the practicability.We believe our work can provide useful insights into current denoising research.The source code is available at https://github.com/cszn/SCUNet....
Swin-Conv-UNet (SCUNet) denoising network The architecture of the proposed Swin-Conv-UNet (SCUNet) denoising network. SCUNet exploits the swin-conv (SC) block as the main building block of a UNet backbone. In each SC block, the input is first passed through a 1×1 convolution, and subsequ...
源代码见:https://github.com/cszn/SCUNet,在线去噪网址见:https://replicate.com/cszn/scunet。 全文导读 Luc Van Gool团队 | 通过Swin-Conv-UNet和数据合成实现实用图像盲去噪 全文下载: Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis https://link.springer.com/article/10.1007/s11...
在去除AGWN和真实图像去噪方面的大量实验表明,新的网络架构设计实现了最先进的性能,新的退化模型则有助于显著提高实用性。该研究希望能够为当前的去噪研究提供有用的见解。源代码见:https://github.com/cszn/SCUNet,在线去噪网址见:https://replicate.com/cszn/scunet。