论文标题
Multiiearth 2022-通过多模式回归和一代的矩阵完成挑战的冠军解决方案
MultiEarth 2022 -- The Champion Solution for the Matrix Completion Challenge via Multimodal Regression and Generation
论文作者
论文摘要
多年来，在不同位置和具有不同方式的光谱带中，地球观察卫星一直在不断监测地球环境。由于复杂的卫星传感条件（例如，天气，云，大气，轨道），可能无法使用某些模式，乐队，位置和时间的观察。 CVPR 2022 [1]中的多学历矩阵完成挑战提供了多模式卫星数据，用于以亚马逊雨林作为感兴趣的地区来解决此类数据稀疏挑战。这项工作提出了自适应的实时多模式回归和生成框架，并在此挑战中以0.2226的LPIP，123.0372的PSNR和0.6347的SSIM在这一挑战中取得了卓越的性能。
Earth observation satellites have been continuously monitoring the earth environment for years at different locations and spectral bands with different modalities. Due to complex satellite sensing conditions (e.g., weather, cloud, atmosphere, orbit), some observations for certain modalities, bands, locations, and times may not be available. The MultiEarth Matrix Completion Challenge in CVPR 2022 [1] provides the multimodal satellite data for addressing such data sparsity challenges with the Amazon Rainforest as the region of interest. This work proposes an adaptive real-time multimodal regression and generation framework and achieves superior performance on unseen test queries in this challenge with an LPIPS of 0.2226, a PSNR of 123.0372, and an SSIM of 0.6347.
