The Multimodal Learning for Earth and Environment Challenge (MultiEarth 2022) will be the first competition aimed at the monitoring and analysis of deforestation in the Amazon rainforest at any time and in any weather conditions. The goal of the Challenge is to provide a common benchmark for multimodal information processing and to bring together the earth and environmental science communities as well as multimodal representation learning communities to compare the relative merits of the various multimodal learning methods to deforestation estimation under well-defined and strictly comparable conditions. MultiEarth 2022 will have three sub-challenges: 1) matrix completion, 2) deforestation estimation, and 3) image-to-image translation. This paper presents the challenge guidelines, datasets, and evaluation metrics for the three sub-challenges. Our challenge website is available at https://sites.google.com/view/rainforest-challenge.
翻译:多模式的地球和环境挑战学习(多地球2022年)将是首次旨在监测和分析在任何时候和任何气候条件下亚马逊雨林毁林现象的竞赛,其目标是为多式信息处理提供一个共同基准,使地球和环境科学界以及多模式代表学习界聚集一堂,在定义明确和严格可比的条件下,比较各种多模式学习方法与毁林估计的相对优点。多地球2022年将有三个次挑战:1)矩阵完成,2)砍伐估计,3)图像到图像翻译。本文介绍了三个次挑战的挑战指南、数据集和评价指标。我们的挑战网站可在https://sites.google.com/view/rainforest-challenge查阅。