Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: HDR-cGAN: Single LDR to HDR Image Translation using Conditional GAN   The prime goal of digital imaging techniques is to reproduce the realistic
appearance of a scene. Low Dynamic Range (LDR) cameras are incapable of
representing the wide dynamic range of the real-world scene. The captured
images turn out to be either too dark (underexposed) or too bright
(overexposed). Specifically, saturation in overexposed regions makes the task
of reconstructing a High Dynamic Range (HDR) image from single LDR image
challenging. In this paper, we propose a deep learning based approach to
recover details in the saturated areas while reconstructing the HDR image. We
formulate this problem as an image-to-image (I2I) translation task. To this
end, we present a novel conditional GAN (cGAN) based framework trained in an
end-to-end fashion over the HDR-REAL and HDR-SYNTH datasets. Our framework uses
an overexposed mask obtained from a pre-trained segmentation model to
facilitate the hallucination task of adding details in the saturated regions.
We demonstrate the effectiveness of the proposed method by performing an
extensive quantitative and qualitative comparison with several state-of-the-art
single-image HDR reconstruction techniques.

36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
16
The categories of this paper are: stat
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio