Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CtlGAN: Few-shot Artistic Portraits Generation with Contrastive Transfer
  Learning   Generating artistic portraits is a challenging problem in computer vision.
Existing portrait stylization models that generate good quality results are
based on Image-to-Image Translation and require abundant data from both source
and target domains. However, without enough data, these methods would result in
overfitting. In this work, we propose CtlGAN, a new few-shot artistic portraits
generation model with a novel contrastive transfer learning strategy. We adapt
a pretrained StyleGAN in the source domain to a target artistic domain with no
more than 10 artistic faces. To reduce overfitting to the few training
examples, we introduce a novel Cross-Domain Triplet loss which explicitly
encourages the target instances generated from different latent codes to be
distinguishable. We propose a new encoder which embeds real faces into Z+ space
and proposes a dual-path training strategy to better cope with the adapted
decoder and eliminate the artifacts. Extensive qualitative, quantitative
comparisons and a user study show our method significantly outperforms
state-of-the-arts under 10-shot and 1-shot settings and generates high quality
artistic portraits. The code will be made publicly available.

6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys