Phrase Grounding

Phrase grounding is a computer vision task that localizes specific objects or regions in an image based on natural language descriptions. Given an image and a text phrase, the system identifies and returns the spatial location of the referenced object as a bounding box.

Instead of training a model to detect pre-defined categories like "car" or "person," you describe what you want ("the red car on the left" or "the person wearing a blue jacket") and the model finds it.

New to Datature Vi?

Datature Vi lets you train a custom VLM for phrase grounding on your own images. Learn what Datature Vi does or follow the quickstart.

Best for

By the end of this guide

Understand how phrase grounding returns bounding boxes for natural language descriptions, enabling flexible object localization without pre-defined categories.

How phrase grounding works

A VLM processes both the image and your text description together through four stages:

Common use cases

Phrase grounding vs. other vision tasks

Task

Input

Output

Best for

Use phrase grounding to locate specific objects. Use visual question answering to understand or analyze image content.

Phrase grounding vs. traditional object detection

Traditional object detection detects pre-defined object classes you specified during training (such as "car" or "person"). It works well for consistent, well-defined categories and high-volume detection of known objects.

Phrase grounding localizes objects based on flexible text descriptions without pre-defined categories. It suits flexible, changing requirements, objects described by attributes or relationships, and interactive or conversational systems.

Example: Traditional detection finds every "car" in the image. Phrase grounding finds "the scratched car on the left conveyor belt."

Tips for better phrase grounding results

Practice

Good example

Avoid

Provide diverse training examples. Vary object types, phrasings, attributes, scene complexity, lighting, and viewpoints. More diversity produces better generalization. See dataset preparation and annotation best practices.

Frequently asked questions

How phrase grounding works in Datature Vi

The workflow for phrase grounding in Datature Vi follows four steps: create a phrase grounding dataset, upload images, annotate with text-linked bounding boxes, and train.

For more on how phrase grounding connects to other Datature Vi concepts, see the Visual Grounding glossary entry.