Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unsupervised motion saliency map estimation based on optical flow
  inpainting   The paper addresses the problem of motion saliency in videos, that is,
identifying regions that undergo motion departing from its context. We propose
a new unsupervised paradigm to compute motion saliency maps. The key ingredient
is the flow inpainting stage. Candidate regions are determined from the optical
flow boundaries. The residual flow in these regions is given by the difference
between the optical flow and the flow inpainted from the surrounding areas. It
provides the cue for motion saliency. The method is flexible and general by
relying on motion information only. Experimental results on the DAVIS 2016
benchmark demonstrate that the method compares favourably with state-of-the-art
video saliency methods.

15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph