Sagar Soni, Akshay Dudhane, et al.
CVPR 2025
The 2025 CVPR EarthVision Data Challenge organized by the Embed2Scale consortium invites researchers to push the boundaries of AI-based compression for Earth observation by developing lossy neural encoders that reduce SSL4EO-S12 (v1.1) data cubes to 1024-dimensional embeddings while preserving downstream analytical utility. Participants engaged in a three-week development phase (March 10–31 2025) submitting solutions via Eval.AI, followed by a one-week testing phase (April 3–5 2025) on a held-out dataset to establish the final leaderboard. The winners’ solutions and insights on the evaluation framework will be presented at the CVPR EarthVision workshop 2025. By rigorously evaluating self-supervised embeddings across diverse hidden tasks, this challenge seeks to advance the state of the art in lossy neural compression and promote transparent, open-science practices in Earth observation foundation modeling.
Sagar Soni, Akshay Dudhane, et al.
CVPR 2025
C.A. Micchelli, W.L. Miranker
Journal of the ACM
Saurabh Paul, Christos Boutsidis, et al.
JMLR
Joxan Jaffar
Journal of the ACM