From ef0eb3c6ee87857b653042be62f99196e45bdf19 Mon Sep 17 00:00:00 2001 From: Chen Liangyu Date: Wed, 20 Apr 2022 00:40:20 +0800 Subject: [PATCH] Update readme.md --- readme.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/readme.md b/readme.md index 0a7a6e6..4529b37 100644 --- a/readme.md +++ b/readme.md @@ -11,7 +11,7 @@ The official pytorch implementation of the paper **[Simple Baselines for Image R >In this paper, we propose a simple baseline that exceeds the SOTA methods and is computationally efficient. >To further simplify the baseline, we reveal that the nonlinear activation functions, e.g. Sigmoid, ReLU, GELU, Softmax, etc. are **not necessary**: they could be replaced by multiplication or removed. Thus, we derive a Nonlinear Activation Free Network, namely NAFNet, from the baseline. SOTA results are achieved on various challenging benchmarks, e.g. 33.69 dB PSNR on GoPro (for image deblurring), exceeding the previous SOTA 0.38 dB with only 8.4% of its computational costs; 40.30 dB PSNR on SIDD (for image denoising), exceeding the previous SOTA 0.28 dB with less than half of its computational costs. -| NAFNet For Image Denoise | NAFNet For Image Deblur | NAFSSR For Stereo Image Super Resolution | +| NAFNet For Image Denoise | NAFNet For Image Deblur | NAFSSR For Stereo Image Super Resolution | | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | | Denoise | Deblur | StereoSR([NAFSSR](https://github.com/megvii-research/NAFNet/blob/main/docs/StereoSR.md)) |