May 25, 2022, 1:12 a.m. | Yifeng Zhou, Xing Xu, Shuaicheng Liu, Guoqing Wang, Huimin Lu, Heng Tao Shen

cs.CV updates on arXiv.org arxiv.org

To achieve promising results on removing noise from real-world images, most
of existing denoising networks are formulated with complex network structure,
making them impractical for deployment. Some attempts focused on reducing the
number of filters and feature channels but suffered from large performance
loss, and a more practical and lightweight denoising network with fast
inference speed is of high demand.


To this end, a \textbf{Thu}mb\textbf{n}ail based \textbf{D}\textbf{e}noising
Netwo\textbf{r}k dubbed Thunder, is proposed and implemented as a lightweight
structure for fast …

arxiv cv denoising image network

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