Unlock the power of video

Video training data, faster than ever. Work with video in its native format from start to finish in your AI development workflow.

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Quickly annotate with precision

Our video editor provides comprehensive labeling tools to classify videos or specific frames. Annotate video data with bounding boxes, polylines, a point, or segmentation masks.

Capture more detail with segmentation masks

Use our video segmentation tool to create pixel-perfect annotations of an object or concept in a video. Easily copy and paste masks across frames for a faster and more precise workflow.

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Label faster than ever with automation

Achieve up to 80% in labeling efficiency gains with model-assisted labeling – use models to pre-label data, and let humans focus on corrective actions to generate ground truth so they don’t need to start from scratch.

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Optimize time and costs with auto labeling

Using dynamic filters operating on the content, metadata, or text embeddings, automatically add a label on matching results at scale and queue them for human review.

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Access the world’s best labeling teams at a click of a button

Access the world’s best data labeling teams to label your data on demand, at scale. The data labeling teams are specialized in use-cases and languages spanning industries such as geospatial, insurance, healthcare and working with content in over 20 languages.

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Create better labels with more context

Bring additional attachments such as text, videos, images, overlays or even custom HTML widgets to aid data labelers to create perfect labels. The Labelbox video editor is optimized to get the most out of your video data, quickly.

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Your toolset to find and fix errors

Easily search for video data using filters such as annotation, metadata, and similarity embeddings to prioritize videos to label or create review tasks to fix issues that matter the most.

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"Labelbox’s video annotation tools are so easy to use. The documentation is accessible, and the labeling pipeline is straightforward. We just had to upload our data, customize the editor to our exact requirements, and go. We had actually budgeted a week to get it set up, but we were done in a day."

Jake Lee

Data Scientist

Jet Propulsion Laboratory