2026 IEEE GRSS Data Fusion Contest: SAR Temporal Storytelling
Winners of the IEEE GRSS 2026 Data Fusion Contest
The organizing committee of the IEEE GRSS 2026 Data Fusion Contest would like to thank all the participants for their submissions. This year’s contest was highly competitive, attracting several high-quality submissions from around the globe. After a rigorous review process based on criteria designed to reward technical rigor, creativity, clarity, and practical relevance, as outlined on the contest website, the evaluation committee has selected four winning entries. In the spirit of this year’s exploratory and qualitative challenge, all four selected submissions are recognized as equal winners. Congratulations on this outstanding achievement!
Winning Entries
Title: Phase Gradient Voting: Unwrap-Free Deformation Screening for Small-Satellite X-Band InSAR Stacks
Authors: Yasuhito Nagase, Josaphat Tetuko Sri Sumantyo
Affiliation: Chiba University, Japan
Title: TRISAR: Self-Supervised Triplet Metric Learning for Temporal SAR Interpretation
Authors: Jamil Jozsef Ghazal, Andras Jung, Vera Konyves
Affiliation: Eötvös Loránd University (ELTE), Hungary/ HUN-REN Institute for Computer Science and Control (SZTAKI), Hungary
Title: T-SAR-JEPA: Temporal Self-Supervised Anomaly Detection in SAR Amplitude Stacks via Latent Prediction
Authors: Kerod Woldesenbet, Abem Woldesenbet
Affiliation: Independent Researcher/Dakota State University
Title FiLM-GPNet: Geometry-Aware Pseudo-Supervised Phase Restoration with Zero-Shot Generalization for Large Temporal InSAR Stacks
Authors: Getnet Demil, Muhammad Farhan Humayun, Tomi Westerlund, Jukka Heikkonen, Mourad Oussalah
Affiliation: University of Oulu, Finland/University of Turku, Finland
The winners will receive their award certificates at IGARSS 2026. They will also present their method at a Community Contributed Theme (CCT) dedicated to the DFC26.
