论文标题
UG2+挑战2022大气湍流缓解的第一名解决方案
1st Place Solutions for UG2+ Challenge 2022 ATMOSPHERIC TURBULENCE MITIGATION
论文作者
论文摘要
在这份技术报告中，我们简要介绍了团队“夏季”的解决方案，以减轻ug $^2 $+ CVPR 2022的挑战。在此任务中，我们提出了一个统一的端到端框架，以从扭曲的帧中重建高质量的图像，这主要由基于rolsormer的基于基于rolsormer的图像模型和基于基于nima的图像组成质量，并构成了一个nima yima yima yima优质量。我们的框架是高效且通用的，它适合热空气图像和文本图案。此外，我们精心构成了超过10万张图像以模拟大气湍流。这些图像改善了模型的鲁棒性。最后，我们在文本模式的重建结果上达到了98.53 \％的平均准确度，在最终排行榜上排名第一。
In this technical report, we briefly introduce the solution of our team ''summer'' for Atomospheric Turbulence Mitigation in UG$^2$+ Challenge in CVPR 2022. In this task, we propose a unified end-to-end framework to reconstruct a high quality image from distorted frames, which is mainly consists of a Restormer-based image reconstruction module and a NIMA-based image quality assessment module. Our framework is efficient and generic, which is adapted to both hot-air image and text pattern. Moreover, we elaborately synthesize more than 10 thousands of images to simulate atmospheric turbulence. And these images improve the robustness of the model. Finally, we achieve the average accuracy of 98.53\% on the reconstruction result of the text patterns, ranking 1st on the final leaderboard.
