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Segment Anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi et al., 2023. Proceedings of ICCV 2023.
Introduces the Segment Anything Model, a general-purpose image segmentation model trained on a very large set of masks that can outline objects from simple prompts such as points or boxes.
What it's used for here
The emerging-methods survey proposes it for unsupervised segmentation of glyphs and figures in the manuscript images.
Cited by on this site 1 record
1 methods surveys
SRCMathematics
Cite it
Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W. Y., Dollár, P., & Girshick, R. (2023). Segment Anything. Proceedings of ICCV 2023. https://arxiv.org/abs/2304.02643
@article{kirillov2023segment,
author = {Kirillov, Alexander and Mintun, Eric and Ravi, Nikhila and Mao, Hanzi and Rolland, Chloe and Gustafson, Laura and Xiao, Tete and Whitehead, Spencer and Berg, Alexander C. and Lo, Wan-Yen and Dollár, Piotr and Girshick, Ross},
title = {Segment Anything},
journal = {Proceedings of ICCV 2023},
year = {2023},
url = {https://arxiv.org/abs/2304.02643}
}TY - JOUR TI - Segment Anything AU - Kirillov, Alexander AU - Mintun, Eric AU - Ravi, Nikhila AU - Mao, Hanzi AU - Rolland, Chloe AU - Gustafson, Laura AU - Xiao, Tete AU - Whitehead, Spencer AU - Berg, Alexander C. AU - Lo, Wan-Yen AU - Dollár, Piotr AU - Girshick, Ross PY - 2023 JO - Proceedings of ICCV 2023 UR - https://arxiv.org/abs/2304.02643 ER -
Kirillov, Alexander et al.. “Segment Anything.” Proceedings of ICCV 2023 (2023).