Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generalized Boundaries from Multiple Image Interpretations   Boundary detection is essential for a variety of computer vision tasks such
as segmentation and recognition. In this paper we propose a unified formulation
and a novel algorithm that are applicable to the detection of different types
of boundaries, such as intensity edges, occlusion boundaries or object category
specific boundaries. Our formulation leads to a simple method with
state-of-the-art performance and significantly lower computational cost than
existing methods. We evaluate our algorithm on different types of boundaries,
from low-level boundaries extracted in natural images, to occlusion boundaries
obtained using motion cues and RGB-D cameras, to boundaries from
soft-segmentation. We also propose a novel method for figure/ground
soft-segmentation that can be used in conjunction with our boundary detection
method and improve its accuracy at almost no extra computational cost.

11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an