Real-World Knowledge-Guided Change Data Synthesis for Remote Sensing

The paper introduces KnowChange, a framework that uses pretrained vision‑language models to guide the synthesis of change data for remote sensing. By reasoning about plausible change locations and class transitions, KnowChange flexibly generates diverse change types within a unified pipeline. Experiments show that data produced by KnowChange outperforms existing synthetic datasets in both synthetic‑to‑real transfer and data augmentation scenarios, even at a compact scale.

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• llms
• multimodal