SlowGuess/NeurIPS_2023_OCR huggingface dataset:
y
(b)
$y$ $(x\in [0.3,1]^n)$
Figure 9: Denoising results for example images of the form  $y = x + \lambda \varepsilon$  with  $\sigma = 25 / 255$  and  $x \in [0,1]^n$ , by FDnCNN [47] specialized for noise level  $\sigma$  only. Here,  $f_{\theta}^{\emptyset}$ ,  $f_{\theta}^{\mathrm{SE}}$  and  $f_{\theta}^{\mathrm{NE}}$  denote the ordinary, scale-equivariant and normalization-equivariant variants, respectively.
Figure 10: Qualitative comparison of image denoising results with synthetic white Gaussian noise for "non-blind" models. Regardless of the variant of a model, the denoising results are visually similar.