Publication
Structured prediction with output embeddings for semantic image annotation
Conference Article
Conference
Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT)
Edition
2016
Pages
552-557
Doc link
https://aclweb.org/anthology/N/N16/N16-1068.pdf
File
Authors
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Quattoni, Ariadna
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Ramisa Ayats, Arnau
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Swaroop Madhyastha, Pranava
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Simo Serra, Edgar
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Moreno Noguer, Francesc
Projects associated
Abstract
We address the task of annotating images with semantic tuples. Solving this problem requires an algorithm able to deal with hundreds of classes for each argument of the tuple. In such contexts, data sparsity becomes a key challenge. We propose handling this sparsity by incorporating feature representations of both the inputs (images) and outputs (argument classes) into a factorized log-linear model.
Categories
computer vision.
Author keywords
natural language processing
Scientific reference
A. Quattoni, A. Ramisa, P. Swaroop, E. Simo-Serra and F. Moreno-Noguer. Structured prediction with output embeddings for semantic image annotation, 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , 2016, San Diego, pp. 552-557.
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