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From LAION-5B to LAION-EO: Filtering Billions of Images Using Anchor Datasets for Satellite Image Extraction

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arxiv 2309.15535 v1 pith:I37ACXRG submitted 2023-09-27 cs.CV cs.AIcs.LG

Mikolaj Czerkawski , Alistair Francis This is my paper · ORCID
classification cs.CVcs.AIcs.LG
keywords datasetextractionimagessatelliteanchordatasetsfilteringimage
verification ladder T0 review T1 audit T2 compute T3 formal
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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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  1. Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation

    cs.CV 2025-07 conditional novelty 6.0 of 10

    A two-stage method (MpGI) produces a 210K-image, 1.26M-caption remote sensing dataset and state-of-the-art CLIP and CoCa models.

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