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Large-scale unsupervised semantic segmentation

Abstract:

Empowered by large datasets, e.g., ImageNet and MS COCO, unsupervised learning on large-scale data has enabled significant advances for classification tasks. However, whether the large-scale unsupervised semantic segmentation can be achieved remains unknown. There are two major challenges: i) we need a large-scale benchmark for assessing algorithms; ii) we need to develop methods to simultaneously learn category and shape representation in an unsupervised manner. In this work, we propose a ne...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/TPAMI.2022.3218275

Authors


Publisher:
IEEE
Journal:
IEEE Transactions on Pattern Analysis and Machine Intelligence More from this journal
Volume:
45
Issue:
6
Pages:
7457 - 7476
Publication date:
2022-10-31
Acceptance date:
2022-10-10
DOI:
EISSN:
1939-3539
ISSN:
0162-8828
Language:
English
Keywords:
Pubs id:
1307995
Local pid:
pubs:1307995
Deposit date:
2023-02-10

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