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All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation

All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2847993503

All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation

About this item

Full title

All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2023-08

Language

English

Formats

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

More information

Scope and Contents

Contents

In this work, we propose a new transformer-based regularization to better localize objects for Weakly supervised semantic segmentation (WSSS). In image-level WSSS, Class Activation Map (CAM) is adopted to generate object localization as pseudo segmentation labels. To address the partial activation issue of the CAMs, consistency regularization is em...

Alternative Titles

Full title

All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2847993503

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2847993503

Other Identifiers

E-ISSN

2331-8422

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