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View Code? Open in Web Editor NEW[TPAMI 2022] DistgSSR: Disentangling Mechanism for Light Field Statial Super-Resolution
[TPAMI 2022] DistgSSR: Disentangling Mechanism for Light Field Statial Super-Resolution
作者,你好,最近看到你的文章,写得非常好,给了我一些启发,于是就想自己复现一下,自己训练了你的网络。通过BasicLF中得到了你的代码,但上采样4倍的结果PSNR与SSIM的平均值与你论文中的结果有较大的差异,PSNR平均值仅仅只有31.74.我用到的训练策略和论文中一样,也是通过你提供在BasicLF中的matlab代码生成的数据集,我思考了蛮久,唯一觉得有错的地方可能就是制作×4的数据集可能有错。
angRes, scale_factor = args.angRes, args.scale_factor
patchsize = scale_factor * 32
stride = patchsize // 2
downRatio = 1 / scale_factor
在matlab设置的stride无论×2或×4的数据集,stride都是使用的32.
想问一下你,×2的和×4的得到的patchsize分别为64和128,那么它们的stride是分别设置为32和64,还是一致设置为32.希望你能给我这个解答,非常感谢。
注意:通过下载你的预训练模型,经过测试得到的结果和你的一样。
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