你好，作者！ 我想请问一下你的采样过程中，你在文章中说“To generate a normally exposed image using a low-light
image, the low-light image is first passed through the encoder to extract the color map g(xl) and then the latent features
of the encoder are used as the condition for the invertible network. For the sampling strategy of z, one can randomly
select a batch of z from the distribution N (g(xL), 1) to get different outputs and then calculate the mean of generated
normally-exposed images to achieve better performance. To speed up the inference, we directly select g(xl) as the input
z and we empirically find that it can achieve a good enough result. So for all the experiments, we just use the mean value
g(xl) as the latent feature z for the conditional normalizing flow if not specified.” 但是我在代码中没有找到使用g(x_l) 均值的部分，我只看到您是直接约束了正常图像colo_map 和编码器的生成结果g(x_l)，请教一下随机性表现在哪里呢。
Lei00764
commented
1 year ago
你好，作者！ 我想请问一下你的采样过程中，你在文章中说“To generate a normally exposed image using a low-light image, the low-light image is first passed through the encoder to extract the color map g(xl) and then the latent features of the encoder are used as the condition for the invertible network. For the sampling strategy of z, one can randomly select a batch of z from the distribution N (g(xL), 1) to get different outputs and then calculate the mean of generated normally-exposed images to achieve better performance. To speed up the inference, we directly select g(xl) as the input z and we empirically find that it can achieve a good enough result. So for all the experiments, we just use the mean value g(xl) as the latent feature z for the conditional normalizing flow if not specified.” 但是我在代码中没有找到使用g(x_l) 均值的部分，我只看到您是直接约束了正常图像colo_map 和编码器的生成结果g(x_l)，请教一下随机性表现在哪里呢。