1st Thermal Image Super Resolution Challenge PBVS-TISR Challenge, CVPR 2020 Call for Papers

1st Thermal Image Super Resolution Challenge PBVS-TISR Challenge, CVPR 2020

http://vcipl-okstate.org/pbvs/20/challenge.html

in conjuntion with the 
16th IEEE Workshop on Perception Beyond the Visible Spectrum (PBVS 2020), 
CVPR 2020

http://vcipl-okstate.org/pbvs/20/

June 2020
Seattle, WA, USA

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Important Dates
    Registration open & datase released: December 10, 2019
    Evaluation images distributed: February 21, 2020
    Deadline for challenge & result submitted: February 28, 2020
    Winner announcement: June 14, 2020

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Objective & Scope

In general, thermal images have a poor resolution, which could be
improved by using learning-based traditional super-resolution
methods. These methods have been largely used in the visible spectral
domain. They work by downsampling and adding noise and blur to the
given image. These noisy and blurred poor quality images, together
with the given images (which are used as the Ground Truths), are used
in the learning process.

The approach mentioned above has been mostly used to tackle the
super-resolution problem, however there are few contributions where
the learning process is based on the usage of a pair of images (low
and a high-resolution images) obtained from different cameras. For the
current challenge, a novel thermal image dataset has been created,
containing images with three different resolutions (low, mid, high)
obtained with three different thermal cameras. The challenge consists
in creating a solution capable of generating super-resolution images
in x2, x3 and x4 scale from each resolution, in the case of x2 an
additional evaluation will be performed by using a HR image obtained
from another camera. The results from each team will be evaluated in
two ways as detailed in the Challenge Web page:


http://vcipl-okstate.org/pbvs/20/challenge.html