MEOX: Compact Multimodal Mixture-of-Experts for Earth Observation
Recent advances in Earth Observation representation learning accommodate heterogeneous sensors and missing observations, often through larger architectures. We present MEOX (Multimodal Earth Observation with eXperts), a multimodal masked autoencoder with a 2.939 million-parameter encoder and 3.115 million parameters in total. Sensor-specific adapters, explicit validity signals, and a shared sparse-expert block preserve modality-dependent processing before a learned patch-wise fusion. Four metadata tokens then accompany a single spatial sequence through fourteen further encoder blocks. Shared expert projections with private low-rank residuals constrain parameter growth, while rotary attent...
| Authors | Mohanad Albughdadi |
|---|---|
| Primary category | cs.CV |
| Published | 4 September 2026 |
| Last updated at source | 14 September 2026 |
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