Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian Joint Modelling for Object Localisation in Weakly Labelled
  Images   We address the problem of localisation of objects as bounding boxes in images
and videos with weak labels. This weakly supervised object localisation problem
has been tackled in the past using discriminative models where each object
class is localised independently from other classes. In this paper, a novel
framework based on Bayesian joint topic modelling is proposed, which differs
significantly from the existing ones in that: (1) All foreground object classes
are modelled jointly in a single generative model that encodes multiple object
co-existence so that "explaining away" inference can resolve ambiguity and lead
to better learning and localisation. (2) Image backgrounds are shared across
classes to better learn varying surroundings and "push out" objects of
interest. (3) Our model can be learned with a mixture of weakly labelled and
unlabelled data, allowing the large volume of unlabelled images on the Internet
to be exploited for learning. Moreover, the Bayesian formulation enables the
exploitation of various types of prior knowledge to compensate for the limited
supervision offered by weakly labelled data, as well as Bayesian domain
adaptation for transfer learning. Extensive experiments on the PASCAL VOC,
ImageNet and YouTube-Object videos datasets demonstrate the effectiveness of
our Bayesian joint model for weakly supervised object localisation.

16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg