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Dense decoder shortcut connections for single-pass semantic segmentation

Abstract:

We propose a novel end-to-end trainable, deep, encoder-decoder architecture for single-pass semantic segmentation. Our approach is based on a cascaded architecture with feature-level long-range skip connections. The encoder incorporates the structure of ResNeXt's residual building blocks and adopts the strategy of repeating a building block that aggregates a set of transformations with the same topology. The decoder features a novel architecture, consisting of blocks, that (i) capture context...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1109/cvpr.2018.00690

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
St Annes College
Publisher:
Institute for Electrical and Electronics Engineers Publisher's website
Publication date:
2018-12-17
DOI:
Pubs id:
pubs:953152
URN:
uri:28896bb0-1090-4e14-9b6a-c9bc82d1a0f6
UUID:
uuid:28896bb0-1090-4e14-9b6a-c9bc82d1a0f6
Local pid:
pubs:953152

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