Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for
  Generative Adversarial Networks   We present a new method for one shot domain adaptation. The input to our
method is trained GAN that can produce images in domain A and a single
reference image I_B from domain B. The proposed algorithm can translate any
output of the trained GAN from domain A to domain B. There are two main
advantages of our method compared to the current state of the art: First, our
solution achieves higher visual quality, e.g. by noticeably reducing
overfitting. Second, our solution allows for more degrees of freedom to control
the domain gap, i.e. what aspects of image I_B are used to define the domain B.
Technically, we realize the new method by building on a pre-trained StyleGAN
generator as GAN and a pre-trained CLIP model for representing the domain gap.
We propose several new regularizers for controlling the domain gap to optimize
the weights of the pre-trained StyleGAN generator to output images in domain B
instead of domain A. The regularizers prevent the optimization from taking on
too many attributes of the single reference image. Our results show significant
visual improvements over the state of the art as well as multiple applications
that highlight improved control.

35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat