Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and
  Indoor Scene Layouts   We develop new representations and algorithms for three-dimensional (3D)
object detection and spatial layout prediction in cluttered indoor scenes. We
first propose a clouds of oriented gradient (COG) descriptor that links the 2D
appearance and 3D pose of object categories, and thus accurately models how
perspective projection affects perceived image gradients. To better represent
the 3D visual styles of large objects and provide contextual cues to improve
the detection of small objects, we introduce latent support surfaces. We then
propose a "Manhattan voxel" representation which better captures the 3D room
layout geometry of common indoor environments. Effective classification rules
are learned via a latent structured prediction framework. Contextual
relationships among categories and layout are captured via a cascade of
classifiers, leading to holistic scene hypotheses that exceed the
state-of-the-art on the SUN RGB-D database.

17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess