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