Earth-OneVision is a unified 2B-parameter RS-MLLM supporting six modalities and nine tasks via FGVLA, SLIS, and PCMA mechanisms plus a 34M QA-pair dataset, reporting competitive or superior benchmark results versus larger models.
Hi -UCD: A Large -scale Dataset for Urban Semantic Change Detection in Remote Sensing Imagery
2 Pith papers cite this work, alongside 40 external citations. Polarity classification is still indexing.
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PerASCD, a foundation-model-driven cascaded gated decoder with a soft semantic consistency loss, reports state-of-the-art Sek scores of 26.11% on SECOND and 65.21% on LandsatSCD.
citing papers explorer
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Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks
Earth-OneVision is a unified 2B-parameter RS-MLLM supporting six modalities and nine tasks via FGVLA, SLIS, and PCMA mechanisms plus a 34M QA-pair dataset, reporting competitive or superior benchmark results versus larger models.
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Foundation Model-Driven Semantic Change Detection in Remote Sensing Imagery
PerASCD, a foundation-model-driven cascaded gated decoder with a soft semantic consistency loss, reports state-of-the-art Sek scores of 26.11% on SECOND and 65.21% on LandsatSCD.