Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Phrase Localization and Visual Relationship Detection with Comprehensive
  Image-Language Cues   This paper presents a framework for localization or grounding of phrases in
images using a large collection of linguistic and visual cues. We model the
appearance, size, and position of entity bounding boxes, adjectives that
contain attribute information, and spatial relationships between pairs of
entities connected by verbs or prepositions. Special attention is given to
relationships between people and clothing or body part mentions, as they are
useful for distinguishing individuals. We automatically learn weights for
combining these cues and at test time, perform joint inference over all phrases
in a caption. The resulting system produces state of the art performance on
phrase localization on the Flickr30k Entities dataset and visual relationship
detection on the Stanford VRD dataset.

3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ