About Supplementary Materials

[zs1314]

Hello! Your work is truly amazing and has given me a lot of inspiration. I would like to ask where I can find supplementary materials? This is very important to me. We will promote and reference your work!

[Aoyama7Hai]

Sorry for responsing so late!
It seems that I haven't receive the email from github which should have been triggered by your issue.
Now you can find our paper and supple from the Springer page:
https://link.springer.com/chapter/10.1007/978-3-031-72940-9_14
and the direct link to supple is:
https://static-content.springer.com/esm/chp%3A10.1007%2F978-3-031-72940-9_14/MediaObjects/635711_1_En_14_MOESM1_ESM.pdf
If you couldn't open the material, please tell us !

[zs1314]

Thank you very much for your help, it's not too late！！ @Aoyama7Hai

[zs1314]

Hello! Thank you for your support! I am very interested in the implementation of "Deraining Impact on Downstream Vision Tasks" mentioned in the supplementary materials. Could you provide some assistance or share some links? Thanks again! @Aoyama7Hai
@Aoyama7Hai

[Aoyama7Hai]

You can start from this link for "objects" detection output for free but a little bit tedious.
Or creating an account for Python pipeline usage in your project.
https://cloud.google.com/vision/docs/drag-and-drop

[zs1314]

Thank you! That's enough! But I still have doubts about the Percentage Score, can you tell me how he calculates it? @Aoyama7Hai

[Aoyama7Hai]

We calculate the score here by merely average the confidence score with the label of "rain" or "water" from the "Label" output by Google cloud vision API.
I think this is a relatively rough method to valid the performance of deraining ability in downstream tasks. You can find some better calculation method based on Google cloud vision API.

[zs1314]

ok! Thank so much!!!!! I am your fan !! Forover! @Aoyama7Hai