Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Secrets of Salient Object Segmentation   In this paper we provide an extensive evaluation of fixation prediction and
salient object segmentation algorithms as well as statistics of major datasets.
Our analysis identifies serious design flaws of existing salient object
benchmarks, called the dataset design bias, by over emphasizing the
stereotypical concepts of saliency. The dataset design bias does not only
create the discomforting disconnection between fixations and salient object
segmentation, but also misleads the algorithm designing. Based on our analysis,
we propose a new high quality dataset that offers both fixation and salient
object segmentation ground-truth. With fixations and salient object being
presented simultaneously, we are able to bridge the gap between fixations and
salient objects, and propose a novel method for salient object segmentation.
Finally, we report significant benchmark progress on three existing datasets of
segmenting salient objects

19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th