Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generative Adversarial Networks with Conditional Neural Movement
  Primitives for An Interactive Generative Drawing Tool   Sketches are abstract representations of visual perception and visuospatial
construction. In this work, we proposed a new framework, Generative Adversarial
Networks with Conditional Neural Movement Primitives (GAN-CNMP), that
incorporates a novel adversarial loss on CNMP to increase sketch smoothness and
consistency. Through the experiments, we show that our model can be trained
with few unlabeled samples, can construct distributions automatically in the
latent space, and produces better results than the base model in terms of shape
consistency and smoothness.

30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
26
The categories of this paper are: bayes-an
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg