Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction
  and An Optimal Training Framework   Lossy compression algorithms are typically designed to achieve the lowest
possible distortion at a given bit rate. However, recent studies show that
pursuing high perceptual quality would lead to increase of the lowest
achievable distortion (e.g., MSE). This paper provides nontrivial results
theoretically revealing that, \textit{1}) the cost of achieving perfect
perception quality is exactly a doubling of the lowest achievable MSE
distortion, \textit{2}) an optimal encoder for the "classic" rate-distortion
problem is also optimal for the perceptual compression problem, \textit{3})
distortion loss is unnecessary for training a perceptual decoder. Further, we
propose a novel training framework to achieve the lowest MSE distortion under
perfect perception constraint at a given bit rate. This framework uses a GAN
with discriminator conditioned on an MSE-optimized encoder, which is superior
over the traditional framework using distortion plus adversarial loss.
Experiments are provided to verify the theoretical finding and demonstrate the
superiority of the proposed training framework.

21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
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
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph