• Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • Cloud tools for web scraping and data extraction Icon
    Cloud tools for web scraping and data extraction

    Deploy pre-built tools that crawl websites, extract structured data, and feed your applications. Reliable web data without maintaining scrapers.

    Automate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
    Explore 10,000+ tools
  • 1
    SVoice (Speech Voice Separation)

    SVoice (Speech Voice Separation)

    We provide a PyTorch implementation of the paper Voice Separation

    ...Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. The repository includes all necessary scripts for training, dataset preparation, distributed training, evaluation, and audio separation.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    CNN for Image Retrieval
    ...It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that can be adapted for custom datasets, making it useful for experimenting with retrieval systems in computer vision. By leveraging CNN architectures, the project showcases how learned embeddings can capture semantic similarity across varied images. This resource serves as both an educational reference and a foundation for further exploration in image retrieval research.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 3
    I3D models trained on Kinetics

    I3D models trained on Kinetics

    Convolutional neural network model for video classification

    ...The models have achieved state-of-the-art results on benchmark datasets such as UCF101 and HMDB51, and also won first place in the CVPR 2017 Charades Challenge. The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs.
    Downloads: 3 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next