# Webpage Segmentation for Extracting Images and Their Surrounding Contextual Information

arXiv: https://arxiv.org/abs/2005.09639 · HTML: https://mlsanity.com/paper/2005.09639/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 May 2020.

## Built on by (most cited first, 1 of 1)

- [Web Image Context Extraction with Graph Neural Networks and Sentence Embeddings on the DOM tree](https://mlsanity.com/paper/2108.11629/) (2021)

## Abstract (arXiv)

Web images come in hand with valuable contextual information. Although this information has long been mined for various uses such as image annotation, clustering of images, inference of image semantic content, etc., insufficient attention has been given to address issues in mining this contextual information. In this paper, we propose a webpage segmentation algorithm targeting the extraction of web images and their contextual information based on their characteristics as they appear on webpages. We conducted a user study to obtain a human-labeled dataset to validate the effectiveness of our method and experiments demonstrated that our method can achieve better results compared to an existing segmentation algorithm.