Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Actions and Attributes from Wholes and Parts   We investigate the importance of parts for the tasks of action and attribute
classification. We develop a part-based approach by leveraging convolutional
network features inspired by recent advances in computer vision. Our part
detectors are a deep version of poselets and capture parts of the human body
under a distinct set of poses. For the tasks of action and attribute
classification, we train holistic convolutional neural networks and show that
adding parts leads to top-performing results for both tasks. In addition, we
demonstrate the effectiveness of our approach when we replace an oracle person
detector, as is the default in the current evaluation protocol for both tasks,
with a state-of-the-art person detection system.

25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
2
The categories of this paper are: math