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PASS-SAM:Integration of Segment Anything Model for Large-Scale Unsupervised Semantic Segmentation

Yin Tang Rui Chen Gensheng Pei Qiong Wang

Computational Visual Media2025，Vol.11Issue(3)：P.669-674,6.

Computational Visual Media2025，Vol.11Issue(3)：P.669-674,6.DOI:10.26599/CVM.2025.9450432

PASS-SAM:Integration of Segment Anything Model for Large-Scale Unsupervised Semantic Segmentation

Yin Tang ¹Rui Chen ¹Gensheng Pei ¹Qiong Wang¹

作者信息

1. School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing,China
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摘要

关键词

segmentation performance/amalgamates benefits various models/segment anything model/pass sam model/segment similar areas/large scale unsupervised semantic segmentation

分类

信息技术与安全科学

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Yin Tang,Rui Chen,Gensheng Pei,Qiong Wang..PASS-SAM:Integration of Segment Anything Model for Large-Scale Unsupervised Semantic Segmentation[J].Computational Visual Media,2025,11(3):P.669-674,6.

Computational Visual Media

ISSN：2096-0433

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