GithubHelp home page GithubHelp logo

Comments (4)

chenyilun95 avatar chenyilun95 commented on July 28, 2024 1

Yes. The global loss is defined to learn the visible keypoints and provide context for RefineNet for hard keypoints prediction.

from tf-cpn.

last-one avatar last-one commented on July 28, 2024

Thanks very much. Do you try to make these keypoints, the valid of which < 1.1, don't generate loss, just like: global loss = (global - target) * (valid > 1.1) as the calculation of refine loss. But now, the global loss = (global - target * (valid > 1.1)). Which one is better? The current solution not only focuses on the visible points, but also wants to make these invisible and non-existing points to be zero.

from tf-cpn.

chenyilun95 avatar chenyilun95 commented on July 28, 2024

About this details I think that is not critical. I think the later ohemlike loss is more important. And the data with valid label 1 is only small part of all.

from tf-cpn.

last-one avatar last-one commented on July 28, 2024

Thanks for your response.

from tf-cpn.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.