<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Datasets | David Vázquez</title><link>https://david-vazquez.com/tags/datasets/</link><atom:link href="https://david-vazquez.com/tags/datasets/index.xml" rel="self" type="application/rss+xml"/><description>Datasets</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://david-vazquez.com/media/icon_hu_a3642885bc94ba2d.png</url><title>Datasets</title><link>https://david-vazquez.com/tags/datasets/</link></image><item><title>BigDocs</title><link>https://david-vazquez.com/project/bigdocs/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://david-vazquez.com/project/bigdocs/</guid><description>&lt;p&gt;BigDocs is a large scale, open, and permissively licensed dataset for training multimodal models on document understanding and code generation tasks. Published at ICLR 2025.&lt;/p&gt;</description></item><item><title>SYNTHIA</title><link>https://david-vazquez.com/project/synthia/</link><pubDate>Wed, 01 Jun 2016 00:00:00 +0000</pubDate><guid>https://david-vazquez.com/project/synthia/</guid><description>&lt;p&gt;SYNTHIA is a large collection of synthetic images for semantic segmentation of urban scenes, generated using a video game engine. Published at CVPR 2016 and widely adopted in the autonomous driving research community. Licensed for commercial use by Intel, Audi, Huawei, Toyota, and Samsung.&lt;/p&gt;</description></item></channel></rss>