Exploring context with deep structured models for semantic segmentation

Exploring context with deep structured models for semantic segmentation

State-of-the-art semantic image segmentation methods are mostly based on training deep convolutional neural networks (CNNs). In this work, we proffer to improve semantic segmentation with the use of contextual information. In particular, we explore patch-patch context and patch-background context in...

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Bibliographic Details
Main Authors: van den Hengel, Anton, Lin, Guosheng, Shen, Chunhua, Reid, Ian
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2019
Subjects:
Convolutional Neural Networks
DRNTU::Engineering::Computer science and engineering
Semantic Segmentation
Online Access:https://hdl.handle.net/10356/106417
http://hdl.handle.net/10220/47945
http://dx.doi.org/10.1109/TPAMI.2017.2708714

Internet

https://hdl.handle.net/10356/106417
http://hdl.handle.net/10220/47945
http://dx.doi.org/10.1109/TPAMI.2017.2708714

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