Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Conditional Image Generation and Manipulation for User-Specified Content   In recent years, Generative Adversarial Networks (GANs) have improved
steadily towards generating increasingly impressive real-world images. It is
useful to steer the image generation process for purposes such as content
creation. This can be done by conditioning the model on additional information.
However, when conditioning on additional information, there still exists a
large set of images that agree with a particular conditioning. This makes it
unlikely that the generated image is exactly as envisioned by a user, which is
problematic for practical content creation scenarios such as generating facial
composites or stock photos. To solve this problem, we propose a single pipeline
for text-to-image generation and manipulation. In the first part of our
pipeline we introduce textStyleGAN, a model that is conditioned on text. In the
second part of our pipeline we make use of the pre-trained weights of
textStyleGAN to perform semantic facial image manipulation. The approach works
by finding semantic directions in latent space. We show that this method can be
used to manipulate facial images for a wide range of attributes. Finally, we
introduce the CelebTD-HQ dataset, an extension to CelebA-HQ, consisting of
faces and corresponding textual descriptions.

29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
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
9
The categories of this paper are: nlin