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2nd Place Solutions for UG2+ Challenge 2022 -- D3^{3}3Net for Mitigating Atmospheric Turbulence from Images

25 August 2022
Sunder Ali Khowaja
I. Lee
Jiseok Yoon
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Abstract

This technical report briefly introduces to the D3^{3}3Net proposed by our team "TUK-IKLAB" for Atmospheric Turbulence Mitigation in UG2+UG2^{+}UG2+ Challenge at CVPR 2022. In the light of test and validation results on textual images to improve text recognition performance and hot-air balloon images for image enhancement, we can say that the proposed method achieves state-of-the-art performance. Furthermore, we also provide a visual comparison with publicly available denoising, deblurring, and frame averaging methods with respect to the proposed work. The proposed method ranked 2nd on the final leader-board of the aforementioned challenge in the testing phase, respectively.

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