MC-E / Deep-Generalized-Unfolding-Networks-for-Image-Restoration

Accepted by CVPR 2022
123 stars 26 forks source link

The training set for training compressive sensing task #9

Open mlkk518 opened 9 months ago

mlkk518 commented 9 months ago

Hi, thanks for your efforts. I reproduced your work with the BSD400 dataset for the compressive sensing task. However, I trained for several days, but the results are far from your reported results. Is there any trick for the training? Thanks very much! (The model parameters are large, while the training images are few. )

MC-E commented 9 months ago

Sorry for the late reply. What's the result of your training?

mlkk518 commented 9 months ago

Thanks for your reply. I finally found that you finetuned your mode with the Div2K. I am sorry to tell you the detailed results. I remember that it is just lower than your results. Thanks a lot. Recently, I am too busy to reply you late. I guess if I finetune  with the Div2k, and a comparebal results may be derived.

Best Regard!

Junhui Li.


---- Replied Message ----
From Chong ***@***.***>
Date 12/01/2023 08:55
To ***@***.***>
Cc ***@***.***>***@***.***>
Subject Re: [MC-E/Deep-Generalized-Unfolding-Networks-for-Image-Restoration] The training set for training compressive sensing task (Issue #9)

Sorry for the late reply. What's the result of your training?


Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you authored the thread.Message ID: <MC-E/Deep-Generalized-Unfolding-Networks-for-Image-Restoration/issues/9/1835209005@github.com>