Xiaoxiang Zhu Receives Best Paper Award at EarthVision Workshop @ CVPR 2025

MCML PI Xiaoxiang Zhu and collaborators received the Best Paper Award at the EarthVision Workshop, held in conjunction with CVPR 2025, for their paper "Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation." The work introduces a foundation model designed to process data from diverse Earth observation sensors within a unified framework.

Panopticon extends foundation models beyond fixed sensor configurations by enabling flexible integration of optical and radar imagery with varying spectral characteristics. By supporting sensor-agnostic learning, the approach improves performance across a wide range of Earth observation tasks and paves the way for more versatile AI systems for environmental monitoring and geospatial analysis.