LAE-1M: Locate Anything on Earth Dataset

LAE-1M (Locate Anything on Earth - 1 Million) is a large-scale open-vocabulary remote sensing object detection dataset introduced in the paper "Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community" (AAAI 2025).

It contains over 1M images with coarse-grained (LAE-COD) and fine-grained (LAE-FOD) annotations, unified in COCO format, enabling zero-shot and few-shot detection in remote sensing.

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Dataset Details

Dataset Description

• Curated by: Jiancheng Pan, Yanxing Liu, Yuqian Fu, Muyuan Ma, Jiahao Li, Danda Pani Paudel, Luc Van Gool, Xiaomeng Huang
• Funded by: ETH Zürich, INSAIT (partial computing support)
• Shared by: LAE-DINO Project Team
• Language(s): Not language-specific; visual dataset
• License: MIT License

Dataset Sources

• Repository: GitHub - LAE-DINO
• Paper: ArXiv 2408.09110, AAAI 2025
• Project Page: LAE Website
• Dataset Download: HuggingFace

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Dataset Structure

All annotations are in COCO JSON format with bounding boxes and categories.

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Uses

Direct Use

• Open-Vocabulary Object Detection in Remote Sensing
• Benchmarking zero-shot and few-shot detection models
• Pretraining large vision-language models

Out-of-Scope Use

• Any tasks requiring personal or sensitive information
• Real-time inference on satellite streams without further optimization

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Quick Start

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("jaychempan/LAE-1M", split="train")

# Access one example
example = dataset[0]
print(example.keys())  # image, annotations, category_id, etc.

# Show the image (requires Pillow)
from PIL import Image
import io

img = Image.open(io.BytesIO(example["image"]))
img.show()