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index.html

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 <p>This webpage is the easiest way to get information on the MVC dataset for all of your research and projects.</p>
 
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-<a id="designer-templates" class="anchor" href="#designer-templates" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a>Designer Templates</h3>
+<a id="designer-templates" class="anchor" href="#designer-templates" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a>Abstract</h3>
 
-<p>We’ve crafted some handsome templates for you to use. Go ahead and click 'Continue to layouts' to browse through them. You can easily go back to edit your page before publishing. After publishing your page, you can revisit the page generator and switch to another theme. Your Page content will be preserved.</p>
+<p>Clothing retrieval and clothing style recognition are important and practical problems. They have drawn a lot of attention in recent years. However, the clothing photos collected in existing datasets are mostly of front- or near-front view. There are no datasets designed to study the influences of different viewing angles on clothing retrieval performance. To address view-invariant clothing retrieval problem properly, we construct a challenge clothing dataset, called Multi-View Clothing dataset. This dataset not only has four different views for each clothing item, but also provides 264 attributes for describing clothing appearance.
+We adopt a state-of-the-art deep learning method to present baseline results for the attribute prediction and clothing retrieval performance. 
+We also evaluate the method on a more difficult setting, cross-view exact clothing item retrieval.
+Our dataset will be made publicly available for further studies towards view-invariant clothing retrieval.</p>
 
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 <a id="creating-pages-manually" class="anchor" href="#creating-pages-manually" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a>Creating pages manually</h3>