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PASS-SAM:Integration of Segment Anything Model for Large-Scale Unsupervised Semantic Segmentation
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作者 Yin Tang Rui Chen +1 位作者 Gensheng Pei Qiong Wang 《Computational Visual Media》 2025年第3期669-674,共6页
Large-scale unsupervised semantic segmentation(LUSS)is a sophisticated process that aims to segment similar areas within an image without relying on labeled training data.While existing methodologies have made substan... Large-scale unsupervised semantic segmentation(LUSS)is a sophisticated process that aims to segment similar areas within an image without relying on labeled training data.While existing methodologies have made substantial progress in this area,there is ample scope for enhancement.We thus introduce the PASS-SAM model,a comprehensive solution that amalgamates the benefits of various models to improve segmentation performance. 展开更多
关键词 segmentation performance amalgamates benefits various models segment anything model pass sam model segment similar areas large scale unsupervised semantic segmentation
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