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View Code? Open in Web Editor NEWCAMixerSR: Only Details Need More “Attention” (CVPR 2024)
Home Page: https://arxiv.org/abs/2402.19289
License: Apache License 2.0
CAMixerSR: Only Details Need More “Attention” (CVPR 2024)
Home Page: https://arxiv.org/abs/2402.19289
License: Apache License 2.0
请问作者,有尝试过对结果再用GAN做些对抗训练吗?就类似REAL-ESRNET & REAL-ESRGAN那样
主要work的是CAMixer,但基本上来说,这篇工作依赖于对于复杂和简单区域采用不同复杂的的计算获得性能改善。如果区域分别不出来的话,可能需要其他指标。因为CAMixer是用图像区域的复杂度进行分类,这个指标也可以换成其他的。如果不要mask那就是相当于一个普通的WSA和卷积的结合,效果类似但计算量比较大。
我试图复现文章中的mask的作用,文章中图4展现了一些图像不同复杂度对应的概率,但是在复现过程中我发现可视化出的mask十分随机,并不能表现出图像的复杂程度,mask的上一步的pred_score也没有我想要的表现。我的问题是想知道作者在可视化图4中的概率和mask与图片复杂度对应关系上使用的是哪一部分的值?这个值应该从整个SR模型中的第几个predictor中得到?Looking forward to your reply, thanks.
i can not find test_pipeline in the code
请问一下,您这个工程中最主要能work的模块是啥,我这里的需要可能跟你不一样,你的是能分出空白的和需要注意力的区域,我这里区分不出来,在空白的区域可能也需要恢复出东西来,怎么解决呢,有推荐地论文吗
Excuse me, I wonder how can I use .pth files in the folder 'pretrained models', and how can I use your model to generate a high-resolution picture?
您好,当我运行训练代码时,出现如标题所示的bug。我想请问HR不应该是在HR里吗,为什么要检测这个HR图片不在lq_paths里呢?我该如何解决这个问题呢?谢谢
The flow_warp file in the basicsr. archs. arch_util directory does not exist
尝试使用Readme中的文件运行然后报错了
code/basicsr文件夹下并没有utils诶
Traceback (most recent call last):
File "/mnt/CAMixerSR/codes/basicsr/test.py", line 4, in
import archs
File "/mnt/CAMixerSR/codes/basicsr/archs/init.py", line 5, in
from basicsr.utils import get_root_logger, scandir
ModuleNotFoundError: No module named 'basicsr'
我试图复现文章中的mask的作用,文章中图4展现了一些图像不同复杂度对应的概率,但是在复现过程中我发现可视化出的mask十分随机,并不能表现出图像的复杂程度,mask的上一步的pred_score也没有我想要的表现。我的问题是想知道作者在可视化图4中的概率和mask与图片复杂度对应关系上使用的是哪一部分的值?这个值应该从整个SR模型中的第几个predictor中得到?Looking forward to your reply, thanks.
Dear developer,
It seems that you only release the code for inference on the test set.
How to infer on real-world images?
Best wishes.
How do I go through the training process?
您好!我对您的工作非常感兴趣,想询问您为什么要在训练时使用gumble softmax,具体是怎么实现的。
thanks for your share, could you please tell us what the diffrence of these model in pretrained_models folders, thank
作者你好,我觉得你们的工作成果相当出色!但是我对论文里的偏移图(offsets)的原理感到不解,为什么Predictor经过几层卷积后得到的offsets和原图扭曲就能得到具有更多信息的窗口?k = x + flow_warp(x, offsets.permute(0, 2, 3, 1), interp_mode='bilinear', padding_mode='border')
另外,在flow_warp()的实现中提到了optical flow,这里的光流要怎么理解,据我所知光流的获取需要相邻帧的图像信息,这里把offsets看作是光流要怎么理解?期待你的解答!
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