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‎2019/07/23/mapillary-research.html

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<!DOCTYPE html>
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<html lang="en-US">
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<meta charset="utf-8">
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<title>Redirecting&hellip;</title>
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<link rel="canonical" href="https://pytorch.org/blog/mapillary-research/">
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<script>location="https://pytorch.org/blog/mapillary-research/"</script>
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<meta http-equiv="refresh" content="0; url=https://pytorch.org/blog/mapillary-research/">
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<h1>Redirecting&hellip;</h1>
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<a href="https://pytorch.org/blog/mapillary-research/">Click here if you are not redirected.</a>
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‎feed.xml

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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.7.3">Jekyll</generator><link href="https://pytorch.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://pytorch.org/" rel="alternate" type="text/html" /><updated>2019-07-23T08:04:46-07:00</updated><id>https://pytorch.org/</id><title type="html">PyTorch Website</title><subtitle>Scientific Computing...</subtitle><author><name>Facebook</name></author><entry><title type="html">Mapillary Research: Seamless Scene Segmentation and In-Place Activated BatchNorm</title><link href="https://pytorch.org/blog/mapillary-research/" rel="alternate" type="text/html" title="Mapillary Research: Seamless Scene Segmentation and In-Place Activated BatchNorm" /><published>2019-07-23T00:00:00-07:00</published><updated>2019-07-23T00:00:00-07:00</updated><id>https://pytorch.org/blog/mapillary-research</id><content type="html" xml:base="https://pytorch.org/blog/mapillary-research/">&lt;p&gt;With roads in developed countries like the US changing up to 15% annually, &lt;a href=&quot;https://www.mapillary.com/&quot;&gt;Mapillary&lt;/a&gt; addresses a growing demand for keeping maps updated by combining images from any camera into a 3D visualization of the world. Mapillary’s independent and collaborative approach enables anyone to collect, share, and use street-level images for improving maps, developing cities, and advancing the automotive industry.&lt;/p&gt;
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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.7.3">Jekyll</generator><link href="https://pytorch.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://pytorch.org/" rel="alternate" type="text/html" /><updated>2019-07-23T08:22:50-07:00</updated><id>https://pytorch.org/</id><title type="html">PyTorch Website</title><subtitle>Scientific Computing...</subtitle><author><name>Facebook</name></author><entry><title type="html">Mapillary Research: Seamless Scene Segmentation and In-Place Activated BatchNorm</title><link href="https://pytorch.org/blog/mapillary-research/" rel="alternate" type="text/html" title="Mapillary Research: Seamless Scene Segmentation and In-Place Activated BatchNorm" /><published>2019-07-23T00:00:00-07:00</published><updated>2019-07-23T00:00:00-07:00</updated><id>https://pytorch.org/blog/mapillary-research</id><content type="html" xml:base="https://pytorch.org/blog/mapillary-research/">&lt;p&gt;With roads in developed countries like the US changing up to 15% annually, &lt;a href=&quot;https://www.mapillary.com/&quot;&gt;Mapillary&lt;/a&gt; addresses a growing demand for keeping maps updated by combining images from any camera into a 3D visualization of the world. Mapillary’s independent and collaborative approach enables anyone to collect, share, and use street-level images for improving maps, developing cities, and advancing the automotive industry.&lt;/p&gt;
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&lt;p&gt;Today, people and organizations all over the world have contributed more than 600 million images toward Mapillary’s mission of helping people understand the world’s places through images and making this data available, with clients and partners including the World Bank, HERE, and Toyota Research Institute.&lt;/p&gt;
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‎redirects.json

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