3rd Multi-modal Aerial View Image Challenge: Sensor Domain Translation - PBVS 2025

Dylan Bowald, Justice Wheelwright, Oliver Nina, Angel Sappa, Riad Hammoud, Erik Blasch, Nathan Inkawhich; Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshops, 2025, pp. 4640-4649

This paper highlights the objectives, metrics and top performers in the 3rd Multi/Cross Modal Aerial Imagery Translation Challenge (MAVIC-T) of the 21st CVPR PBVS workshop. The core goal of this competition remains the seeding of innovative model development for translating registered aerial images between diverse sensor modalities. Specifically, the challenge explores the transformation between synthetic aperture radar (SAR), electro-optical (EO), visible light (RGB), and infrared (IR) imagery in challenging real world conditions. The competition once again judges its entrants using a composite of the L1-norm, Learned Perceptual Image Patch Similarity (LPIPS), and the Frechet Inception Distance (FID). An additional penalty for overfitting to one domain ups the challenge from 2024, while pushing for more generalizable solutions on the second year return of the Multi Modal Aerial Gathered Image Composite Stacks (MAGIC-STACKS) Dataset. Overall, this year saw 103 total participants. The top performers scored comparably overall to last year's winners, however, there was a notable improvement this year in the RGB to IR translation task. Interestingly, the winning team - up6 was not the best across all translation scenarios, signaling room for improvement in coming years.