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3D60 (Up Viewpoint)

Zioulis, Nikolaos; Karakottas, Antonis; Zarpalas, Dimitrios; Daras, Petros


MARC21 XML Export

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    <subfield code="a">Instructions, code and data splits available @ https://vcl3d.github.io/3D60/</subfield>
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    <subfield code="a">&lt;p&gt;Modern 3D vision advancements rely on data driven methods and thus, task specific annotated datasets. Especially for geometric inference tasks like depth and surface estimation, the collection of high quality data is very challenging, expensive and laborious. While considerable efforts have been made for traditional pinhole cameras, the same cannot be said for omnidirectional ones.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;3D60&lt;/strong&gt;&amp;nbsp;is a collective dataset generated in the context of various 360&lt;sup&gt;o&lt;/sup&gt;&amp;nbsp;vision research works. It comprises multi-modal omnidirectional stereo renders of scenes from realistic and synthetic large-scale 3D datasets (&lt;em&gt;Matterport3D&lt;/em&gt;,&amp;nbsp;&lt;em&gt;Stanford2D3D&amp;nbsp;&lt;/em&gt;and&amp;nbsp;&lt;em&gt;SunCG&lt;/em&gt;).&lt;/p&gt;

&lt;p&gt;Our dataset fills a very important gap in data-driven spherical 3D vision and, more specifically, for the monocular and stereo dense depth and surface estimation tasks.&lt;/p&gt;

&lt;p&gt;We originate by exploiting the efforts made in providing synthetic and real scanned 3D datasets of interior spaces and re-using them via ray-tracing in order to generate high quality, densely annotated spherical panoramas.&lt;/p&gt;</subfield>
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    <subfield code="a">Zarpalas, Dimitrios</subfield>
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    <subfield code="a">Omnidirectional Image</subfield>
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    <subfield code="a">Omnidirectional Stereo</subfield>
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    <subfield code="a">Stereo Vision</subfield>
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    <subfield code="a">Depth Estimation</subfield>
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    <subfield code="a">Surface Estimation</subfield>
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    <subfield code="a">Synthetic Data</subfield>
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    <subfield code="a">Indoor Scenes</subfield>
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    <subfield code="a">Scene Understanding</subfield>
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    <subfield code="a">Enriching 360 media with 3D storytelling and personalisation elements</subfield>
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Data volume 1.3 TB1.3 TB
Unique views 271271
Unique downloads 129129

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