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ImageBind

ImageBind

ImageBind is an open-source AI model from Meta AI that is capable of binding information from six modalities into a single embedding without explicit supervision.

OverviewStructured DataIssuesContributors

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imagebind.metademolab.com
Is a
Product
Product

Product attributes

Launch Date
May 9, 2023
Industry
Artificial Intelligence (AI)
Artificial Intelligence (AI)
Computer Vision
Computer Vision
Machine learning
Machine learning
Generative AI
Generative AI
Natural language processing (NLP)
Natural language processing (NLP)
Product Parent Company
Meta AI
Meta AI

Other attributes

Announcement URL
ai.facebook.com/blog/im...ding-ai/
Overview

ImageBind is an open-source AI model from Meta AI that is capable of binding information from six modalities into a single embedding without explicit supervision. While previous models have combined text, image/video, and audio data, ImageBind also includes depth (3D), thermal (infrared radiation), and inertial measurement units (IMU) that calculate motion and position. Meta states ImageBind is the first AI model to combine all these types of data. With these six modalities, ImageBind makes it possible to identify objects in a photo with their natural language name or description, determine how they will sound, their 3D shape, how warm or cold they are, and how they will move.

Meta AI introduced ImageBind on May 9, 2023, with a blog describing the model and a research paper titled "ImageBind: One Embedding Space To Bind Them All," going into more technical detail. As an open-source model, its code is available on GitHub.

In a demo of the model accompanying its release, Meta shows how ImageBind can do the following:

  • Suggest audio clips for input images or videos
  • Output images based on audio clips
  • Provide image and audio clips based on a natural language input
  • Offer related images for a combined audio/image input

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Further Resources

Title
Author
Link
Type
Date

ImageBind: One Embedding Space To Bind Them All

Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra

https://arxiv.org/abs/2305.05665

May 9, 2023

References

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