Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using
  Stochastic Inference   The main obstacle to weakly supervised semantic image segmentation is the
difficulty of obtaining pixel-level information from coarse image-level
annotations. Most methods based on image-level annotations use localization
maps obtained from the classifier, but these only focus on the small
discriminative parts of objects and do not capture precise boundaries.
FickleNet explores diverse combinations of locations on feature maps created by
generic deep neural networks. It selects hidden units randomly and then uses
them to obtain activation scores for image classification. FickleNet implicitly
learns the coherence of each location in the feature maps, resulting in a
localization map which identifies both discriminative and other parts of
objects. The ensemble effects are obtained from a single network by selecting
random hidden unit pairs, which means that a variety of localization maps are
generated from a single image. Our approach does not require any additional
training steps and only adds a simple layer to a standard convolutional neural
network; nevertheless it outperforms recent comparable techniques on the Pascal
VOC 2012 benchmark in both weakly and semi-supervised settings.

25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph