Structured Prediction with Output Embeddings for Semantic Image Annotation
Ariadna Quattoni, Arnau Ramisa, Pranava Swaroop Madhyastha, Edgar Simo-Serra, Francesc Moreno-Noguer
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.
NAACL, San Diego, USA, June 12-17, 2016.