MultiEarth 2022 -- Multimodal Learning for Earth and Environment Workshop and Challenge
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Image-to-Image TranslationMatrix CompletionRepresentation LearningTranslationSimilar Papers 제목 키워드 기반
MultiEarth 2023 -- Multimodal Learning for Earth and Environment Workshop and Challenge
The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2023) is the second annual CVPR workshop aimed at the monitoring and analysis of the health of Earth ecosystems by leveraging the vast amount of remo…
Representation Learning1st Place Solution to MultiEarth 2023 Challenge on Multimodal SAR-to-EO Image Translation
The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2023) aims to harness the substantial amount of remote sensing data gathered over extensive periods for the monitoring and analysis of Earth's ecosys…
Image EnhancementTranslationMultiEarth 2022 -- The Champion Solution for the Matrix Completion Challenge via Multimodal Regression and Generation
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., weath…
Earth ObservationMatrix CompletionregressionSSIMMultiEarth 2022 -- The Champion Solution for Image-to-Image Translation Challenge via Generation Models
The MultiEarth 2022 Image-to-Image Translation challenge provides a well-constrained test bed for generating the corresponding RGB Sentinel-2 imagery with the given Sentinel-1 VV & VH imagery. In this challenge, we desig…
Image-to-Image TranslationTranslationA Strategy Optimized Pix2pix Approach for SAR-to-Optical Image Translation Task
This technical report summarizes the analysis and approach on the image-to-image translation task in the Multimodal Learning for Earth and Environment Challenge (MultiEarth 2022). In terms of strategy optimization, cloud…
Crop ClassificationImage-to-Image TranslationTime Series AnalysisTime Series Classification+1