Showing 2 open source projects for "benchmark"

View related business solutions
  • $300 Free Credits for Your Google Cloud Projects Icon
    $300 Free Credits for Your Google Cloud Projects

    Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.

    Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
    Start Free Trial
  • AI-powered service management for IT and enterprise teams Icon
    AI-powered service management for IT and enterprise teams

    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
    Try it Free
  • 1
    YouTube-8M

    YouTube-8M

    Starter code for working with the YouTube-8M dataset

    ...The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured at ICCV 2019), enabling researchers and practitioners to benchmark video classification models on large-scale datasets with over millions of labeled videos. The code demonstrates how to process frame-level features, train logistic and deep learning models, evaluate them using metrics like global Average Precision (gAP) and mean Average Precision (mAP), and export trained models for MediaPipe inference.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    Video Nonlocal Net

    Video Nonlocal Net

    Non-local Neural Networks for Video Classification

    ...Efficient implementations keep memory and compute manageable so the blocks can be added without rewriting the entire backbone. The result is a practical, drop-in mechanism for upgrading purely local video models into context-aware networks with strong benchmark performance.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo