RSRCC (A Remote Sensing Regional Change Comprehension Benchmark Constructed via Retrieval Augmented Best of N Ranking) This repository hosts the RSRCC dataset introduced in RSRCC paper. The dataset is designed for semantic change understanding in remote sensing, pairing multi temporal image evidence with natural language questions and answers. 🛰️ This work was done by the RSFM (Remote Sensing Foundation Models) team from Google Research . Official GitHub: https://github.com/google research/remote sensing/ 🛰️ Overview Traditional change detection focuses on identifying where a change occurred between two images. In contrast, semantic change captioning aims to explain what changed in natural language. RSRCC was created to support this richer understanding of temporal change in remote sensing scenes. The dataset contains paired before and after satellite images together with generated language annotations that describe meaningful changes, including examples such as: new construction demolition road or sidewalk changes vegetation changes residential development ✨ Key Features Semantic change understanding: Goes beyond binary change masks by emphasizing language based interpretation o…
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