MultiEarth 2022 -- The Champion Solution for Image-to-Image Translation Challenge via Generation Models

TL;DR

This paper presents the winning solution for the MultiEarth 2022 challenge, using advanced image-to-image translation models like SPADE and pix2pixHD to generate high-quality Sentinel-2 imagery from Sentinel-1 data.

Contribution

It introduces effective generation models for satellite image translation, achieving top performance in the challenge with the SPADE-2 model and L1-loss.

Findings

SPADE-2 with L1-loss achieved 0.02194 MAE score

Best model achieved 0.02795 MAE score

Ranked No.1 on the challenge leaderboard

Abstract

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 designed various generation models and found the SPADE [1] and pix2pixHD [2] models could perform our best results. In our self-evaluation, the SPADE-2 model with L1-loss can achieve 0.02194 MAE score and 31.092 PSNR dB. In our final submission, the best model can achieve 0.02795 MAE score ranked No.1 on the leader board.