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Agentic Object Detection: Finding Objects From a Text Prompt, No Labels

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x.com
Date
Andrew Ng@AndrewYNg
Thread · 2 parts

Introducing Agentic Object Detection! Given a text prompt like “unripe strawberries” or “Kellogg’s branded cereal” and an image, we use an agentic workflow to reason at length and detect the specified objects. No need to label any training data. Watch the video for details.

You can also play with the demo here: https://t.co/3kZJPmwUD4

Context

Agentic Object Detection lets a user specify what to locate in an image with a short description. Andrew Ng's announcement gives unripe strawberries as an example and says users need not label training examples for the requested task.

LandingAI's technical explanation, published later that month, describes planning, code generation and to reason about the image. The output is a set of boxes locating detected objects. That makes the capability useful for requests combining an object with an attribute, rather than merely asking for a general image description. This describes the vendor's supported interface and intended use; it does not establish accuracy on a reader's own images.

Terms in this piece · Glossary
  • tool use — A model's ability to call external functions — run code, search the web, edit files — instead of only generating text.
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