Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Visual Attention for Behavioral Cloning in Autonomous Driving   The goal of our work is to use visual attention to enhance autonomous driving
performance. We present two methods of predicting visual attention maps. The
first method is a supervised learning approach in which we collect eye-gaze
data for the task of driving and use this to train a model for predicting the
attention map. The second method is a novel unsupervised approach where we
train a model to learn to predict attention as it learns to drive a car.
Finally, we present a comparative study of our results and show that the
supervised approach for predicting attention when incorporated performs better
than other approaches.

10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph