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Deep Structured Scene Parsing by Learning with Image Descriptions
[article]
2018
arXiv
pre-print
This paper addresses a fundamental problem of scene understanding: How to parse the scene image into a structured configuration (i.e., a semantic object hierarchy with object interaction relations) that finely accords with human perception. We propose a deep architecture consisting of two networks: i) a convolutional neural network (CNN) extracting the image representation for pixelwise object labeling and ii) a recursive neural network (RNN) discovering the hierarchical object structure and
arXiv:1604.02271v3
fatcat:laaiypmr7bcprixffwbgku22ja