Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Quality Metric Guided Portrait Line Drawing Generation from Unpaired
  Training Data   Face portrait line drawing is a unique style of art which is highly abstract
and expressive. However, due to its high semantic constraints, many existing
methods learn to generate portrait drawings using paired training data, which
is costly and time-consuming to obtain. In this paper, we propose a novel
method to automatically transform face photos to portrait drawings using
unpaired training data with two new features; i.e., our method can (1) learn to
generate high quality portrait drawings in multiple styles using a single
network and (2) generate portrait drawings in a "new style" unseen in the
training data. To achieve these benefits, we (1) propose a novel quality metric
for portrait drawings which is learned from human perception, and (2) introduce
a quality loss to guide the network toward generating better looking portrait
drawings. We observe that existing unpaired translation methods such as
CycleGAN tend to embed invisible reconstruction information indiscriminately in
the whole drawings due to significant information imbalance between the photo
and portrait drawing domains, which leads to important facial features missing.
To address this problem, we propose a novel asymmetric cycle mapping that
enforces the reconstruction information to be visible and only embedded in the
selected facial regions. Along with localized discriminators for important
facial regions, our method well preserves all important facial features in the
generated drawings. Generator dissection further explains that our model learns
to incorporate face semantic information during drawing generation. Extensive
experiments including a user study show that our model outperforms
state-of-the-art methods.

19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
14
The categories of this paper are: math-ph
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph