Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SwiftSRGAN -- Rethinking Super-Resolution for Efficient and Real-time
  Inference   In recent years, there have been several advancements in the task of image
super-resolution using the state of the art Deep Learning-based architectures.
Many super-resolution-based techniques previously published, require high-end
and top-of-the-line Graphics Processing Unit (GPUs) to perform image
super-resolution. With the increasing advancements in Deep Learning approaches,
neural networks have become more and more compute hungry. We took a step back
and, focused on creating a real-time efficient solution. We present an
architecture that is faster and smaller in terms of its memory footprint. The
proposed architecture uses Depth-wise Separable Convolutions to extract
features and, it performs on-par with other super-resolution GANs (Generative
Adversarial Networks) while maintaining real-time inference and a low memory
footprint. A real-time super-resolution enables streaming high resolution media
content even under poor bandwidth conditions. While maintaining an efficient
trade-off between the accuracy and latency, we are able to produce a comparable
performance model which is one-eighth (1/8) the size of super-resolution GANs
and computes 74 times faster than super-resolution GANs.

37
The categories of this paper are: supr-con
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph