Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images
  with Latent Variable Model   Nowadays, driven by the increasing concern on diet and health, food computing
has attracted enormous attention from both industry and research community. One
of the most popular research topics in this domain is Food Retrieval, due to
its profound influence on health-oriented applications. In this paper, we focus
on the task of cross-modal retrieval between food images and cooking recipes.
We present Modality-Consistent Embedding Network (MCEN) that learns
modality-invariant representations by projecting images and texts to the same
embedding space. To capture the latent alignments between modalities, we
incorporate stochastic latent variables to explicitly exploit the interactions
between textual and visual features. Importantly, our method learns the
cross-modal alignments during training but computes embeddings of different
modalities independently at inference time for the sake of efficiency.
Extensive experimental results clearly demonstrate that the proposed MCEN
outperforms all existing approaches on the benchmark Recipe1M dataset and
requires less computational cost.

3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
36
The categories of this paper are: cmp-lg
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The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph
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The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
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The categories of this paper are: cond-mat
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The categories of this paper are: astro-ph
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The categories of this paper are: patt-sol