Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[2022 spring] ICCV 2021 LabOR(20213320) #481

Open
sky0701 opened this issue May 21, 2022 · 1 comment
Open

[2022 spring] ICCV 2021 LabOR(20213320) #481

sky0701 opened this issue May 21, 2022 · 1 comment

Comments

@sky0701
Copy link

sky0701 commented May 21, 2022

좋은 리뷰 감사합니다. PPL와 SPL 사이의 성능 차이가 어디서 기인하는지 궁금합니다. 두 방법에서 실질적으로 라벨링 하는 영역의 면적이 같을때에도 성능 차이가 생길지 궁금하고, 이에 대해 어떻게 생각하시는지 궁금합니다.

@wonjeongchoi
Copy link

Thank you for your good review with some useful notes in figures.
I think your review has good structure and detailed explanation.

However, sentences in your korean version review are so difficult to understand for me.
I guess it is a translated version of english review by using some translator systems..
The overall sentences are quite unnatural and they often have needless punctuation marks.
First of all, I highly recommend you to revise your korean version review with understanable 'korean' sentences.

In the details of methods section(3.2), it would be better if some additional explanations of each loss function are provided.
There are quite a lot of losses and each loss has distinctive goal to train model. How about providing what they do and how they work?

Thank you

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants