Code Monkey home page Code Monkey logo

Comments (3)

kracwarlock avatar kracwarlock commented on June 9, 2024

HMDB-51 provides three train-test splits . We just used split 1. Hollywood2 also provides a train-test split. For validation we used 15% of the training data as validation set and the rest 85% for training. We noted the cost at best performance on the validation set. We then trained on the entire training data until the cost reached the same value as noted with the validation set separated.
Will share the txt files.

from action-recognition-visual-attention.

WeihongM avatar WeihongM commented on June 9, 2024

@kracwarlock Hi, also hope you can share your txt files, Thanks

from action-recognition-visual-attention.

mpkuse avatar mpkuse commented on June 9, 2024

I am trying to figure out how was the 1st attention initialized. In the attached figure, l1?

image

from action-recognition-visual-attention.

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.