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Short Communication | Open Access

PASS-SAM: Integration of segment anything model for large-scale unsupervised semantic segmentation

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

* Yin Tang and Rui Chen contributed equally to this work.

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Computational Visual Media
Pages 669-674

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Cite this article:
Tang Y, Chen R, Pei G, et al. PASS-SAM: Integration of segment anything model for large-scale unsupervised semantic segmentation. Computational Visual Media, 2025, 11(3): 669-674. https://doi.org/10.26599/CVM.2025.9450432

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Received: 20 November 2023
Accepted: 12 April 2024
Published: 19 May 2025
© The Author(s) 2025.

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