mlsanityData to 14 Oct 2026

MultiEarth 2022 -- The Champion Solution for the Matrix Completion Challenge via Multimodal Regression and Generation

arXiv 2206.08970 ↗First posted 17 Jun 2022cs.CVcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 5 references that are in the map. First posted on arXiv 17 Jun 2022.

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References · 2

  1. 2019Semantic Image Synthesis with Spatially-Adaptive Normalizationcited by 1,299
  2. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,179

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