Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DeepPhys: Video-Based Physiological Measurement Using Convolutional
  Attention Networks   Non-contact video-based physiological measurement has many applications in
health care and human-computer interaction. Practical applications require
measurements to be accurate even in the presence of large head rotations. We
propose the first end-to-end system for video-based measurement of heart and
breathing rate using a deep convolutional network. The system features a new
motion representation based on a skin reflection model and a new attention
mechanism using appearance information to guide motion estimation, both of
which enable robust measurement under heterogeneous lighting and major motions.
Our approach significantly outperforms all current state-of-the-art methods on
both RGB and infrared video datasets. Furthermore, it allows spatial-temporal
distributions of physiological signals to be visualized via the attention
mechanism.

28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg