Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Coherent Online Video Style Transfer   Training a feed-forward network for fast neural style transfer of images is
proven to be successful. However, the naive extension to process video frame by
frame is prone to producing flickering results. We propose the first end-to-end
network for online video style transfer, which generates temporally coherent
stylized video sequences in near real-time. Two key ideas include an efficient
network by incorporating short-term coherence, and propagating short-term
coherence to long-term, which ensures the consistency over larger period of
time. Our network can incorporate different image stylization networks. We show
that the proposed method clearly outperforms the per-frame baseline both
qualitatively and quantitatively. Moreover, it can achieve visually comparable
coherence to optimization-based video style transfer, but is three orders of
magnitudes faster in runtime.

20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga