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arXiv · 2304.02643

Segment Anything

Alexander Kirillov·Eric Mintun·Nikhila Ravi·Hanzi Mao·Chloe Rolland·Laura Gustafson·Tete Xiao·Spencer Whitehead·Alexander C. Berg·Wan-Yen Lo·Piotr Dollár·Ross Girshick
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Abstract

We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest segmentation dataset to date (by far), with over 1 billion masks on 11M licensed and privacy respecting images. The model is designed and trained to be promptable, so it can transfer zero-shot to new image distributions and tasks. We evaluate its capabilities on numerous tasks and find that its zero-shot performance is impressive -- often competitive with or even superior to prior fully supervised results. We are releasing the Segment Anything Model (SAM) and corresponding dataset (SA-1B) of 1B masks and 11M images at https://segment-anything.com to foster research into foundation models for computer vision.

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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, Ross Girshick. 2023-04-05. Segment Anything. https://arxiv.org/abs/2304.02643

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