Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stabilizing GANs with Soft Octave Convolutions   Motivated by recently published methods using frequency decompositions of
convolutions (e.g. Octave Convolutions), we propose a novel convolution scheme
to stabilize the training and reduce the likelihood of a mode collapse. The
basic idea of our approach is to split convolutional filters into additive high
and low frequency parts, while shifting weight updates from low to high during
the training. Intuitively, this method forces GANs to learn low frequency
coarse image structures before descending into fine (high frequency) details.
We also show, that the use of the proposed soft octave convolutions reduces
common artifacts in the frequency domain of generated images. Our approach is
orthogonal and complementary to existing stabilization methods and can simply
be plugged into any CNN based GAN architecture. Experiments on the CelebA
dataset show the effectiveness of the proposed method.

34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
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The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
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The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
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The categories of this paper are: bayes-an
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The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
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The categories of this paper are: atom-ph
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an