Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Patch Learning for Weakly Supervised Object Classification and
  Discovery   Patch-level image representation is very important for object classification
and detection, since it is robust to spatial transformation, scale variation,
and cluttered background. Many existing methods usually require fine-grained
supervisions (e.g., bounding-box annotations) to learn patch features, which
requires a great effort to label images may limit their potential applications.
In this paper, we propose to learn patch features via weak supervisions, i.e.,
only image-level supervisions. To achieve this goal, we treat images as bags
and patches as instances to integrate the weakly supervised multiple instance
learning constraints into deep neural networks. Also, our method integrates the
traditional multiple stages of weakly supervised object classification and
discovery into a unified deep convolutional neural network and optimizes the
network in an end-to-end way. The network processes the two tasks object
classification and discovery jointly, and shares hierarchical deep features.
Through this jointly learning strategy, weakly supervised object classification
and discovery are beneficial to each other. We test the proposed method on the
challenging PASCAL VOC datasets. The results show that our method can obtain
state-of-the-art performance on object classification, and very competitive
results on object discovery, with faster testing speed than competitors.

3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
21
The categories of this paper are: adap-org
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess