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

arXiv: https://arxiv.org/abs/2309.15535 · HTML: https://mlsanity.com/paper/2309.15535/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 14 references that are in the map.
- First posted on arXiv 27 Sep 2023.

## Builds on (most cited first, 12 of 12)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding](https://mlsanity.com/paper/2205.11487/) (2022)
- [Zero-Shot Text-to-Image Generation](https://mlsanity.com/paper/2102.12092/) (2021)
- [LAION-5B: An open large-scale dataset for training next generation image-text models](https://mlsanity.com/paper/2210.08402/) (2022)
- [DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation](https://mlsanity.com/paper/2208.12242/) (2022)
- [Billion-scale similarity search with GPUs](https://mlsanity.com/paper/1702.08734/) (2017)
- [An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion](https://mlsanity.com/paper/2208.01618/) (2022)
- [Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training](https://mlsanity.com/paper/2301.02280/) (2023)
- [T-MARS: Improving Visual Representations by Circumventing Text Feature Learning](https://mlsanity.com/paper/2307.03132/) (2023)
- [Open High-Resolution Satellite Imagery: The WorldStrat Dataset -- With Application to Super-Resolution](https://mlsanity.com/paper/2207.06418/) (2022)

## Built on by (most cited first, 14 of 14)

- [On the Foundations of Earth and Climate Foundation Models](https://mlsanity.com/paper/2405.04285/) (2024)
- [Major TOM: Expandable Datasets for Earth Observation](https://mlsanity.com/paper/2402.12095/) (2024)
- [Mind the Modality Gap: Towards a Remote Sensing Vision-Language Model via Cross-modal Alignment](https://mlsanity.com/paper/2402.09816/) (2024)
- [Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space](https://mlsanity.com/paper/2412.05600/) (2024)
- [Instance-Level Composed Image Retrieval](https://mlsanity.com/paper/2510.25387/) (2025)
- [Exploring the Capability of Text-to-Image Diffusion Models with Structural Edge Guidance for Multi-Spectral Satellite Image Inpainting](https://mlsanity.com/paper/2311.03008/) (2023)
- [Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation](https://mlsanity.com/paper/2507.16716/) (2025)
- [GAIA: A Global, Multi-modal, Multi-scale Vision-Language Dataset for Remote Sensing Image Analysis](https://mlsanity.com/paper/2502.09598/) (2025)
- [MESA: Text-Driven Terrain Generation Using Latent Diffusion and Global Copernicus Data](https://mlsanity.com/paper/2504.07210/) (2025)
- [Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection](https://mlsanity.com/paper/2311.06222/) (2023)
- [COP-GEN-Beta: Unified Generative Modelling of COPernicus Imagery Thumbnails](https://mlsanity.com/paper/2504.08548/) (2025)
- [Quantum Machine Learning for Remote Sensing: Exploring potential and challenges](https://mlsanity.com/paper/2311.07626/) (2023)
- [Ai4Fapar: How artificial intelligence can help to forecast the seasonal earth observation signal](https://mlsanity.com/paper/2402.06684/) (2024)
- [Leveraging Multi-Temporal Sentinel 1 and 2 Satellite Data for Leaf Area Index Estimation With Deep Learning](https://mlsanity.com/paper/2410.19787/) (2024)

## Abstract (arXiv)

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.