A two-stage method (MpGI) produces a 210K-image, 1.26M-caption remote sensing dataset and state-of-the-art CLIP and CoCa models.
From LAION-5B to LAION-EO: Filtering Billions of Images Using Anchor Datasets for Satellite Image Extraction
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abstract
Large datasets, such as LAION-5B, contain a diverse distribution of images shared online. However, extraction of domain-specific subsets of large image corpora is challenging. The extraction approach based on an anchor dataset, combined with further filtering, is proposed here and demonstrated for the domain of satellite imagery. This results in the release of LAION-EO, a dataset sourced from the web containing pairs of text and satellite images in high (pixel-wise) resolution. The paper outlines the acquisition procedure as well as some of the features of the dataset.
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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation
A two-stage method (MpGI) produces a 210K-image, 1.26M-caption remote sensing dataset and state-of-the-art CLIP and CoCa models.