Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: What Catches the Eye? Visualizing and Understanding Deep Saliency Models   Deep convolutional neural networks have demonstrated high performances for
fixation prediction in recent years. How they achieve this, however, is less
explored and they remain to be black box models. Here, we attempt to shed light
on the internal structure of deep saliency models and study what features they
extract for fixation prediction. Specifically, we use a simple yet powerful
architecture, consisting of only one CNN and a single resolution input,
combined with a new loss function for pixel-wise fixation prediction during
free viewing of natural scenes. We show that our simple method is on par or
better than state-of-the-art complicated saliency models. Furthermore, we
propose a method, related to saliency model evaluation metrics, to visualize
deep models for fixation prediction. Our method reveals the inner
representations of deep models for fixation prediction and provides evidence
that saliency, as experienced by humans, is likely to involve high-level
semantic knowledge in addition to low-level perceptual cues. Our results can be
useful to measure the gap between current saliency models and the human
inter-observer model and to build new models to close this gap.

25
The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph