articleOct 1, 2023Closed access

Segment Anything

Indexed incrossref

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…

Citation impact

8,852
total citations
FWCI
1005.17
Percentile
100%
References
77
Citations per year

Authors

12

Topics & keywords

Keywords
  • Computer science
  • Segmentation
  • Task (project management)
  • Artificial intelligence
  • Shot (pellet)
  • Image (mathematics)
  • Image segmentation
  • Computer vision
No related works found for this paper.