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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<meta name="description" content="">
<meta name="author" content="">
<title>Detecting Objects in Aerial Images (DOAI)</title>
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<div class="site-heading m-head">
<h2 style="text-align:center; margin-top:60px; font-weight: bold;">
The 1st Workshop on
</h2>
<h1 style="text-align:center; font-weight: bold; color:#FF9900">
Detecting Objects in Aerial Images
</h1>
<!-- <h2>Detecting Objects in Aerial Images (DOAI)</h2> -->
<h2 style="text-align:center; font-weight: bold; font-style: italic">
in conjunction with IEEE CVPR 2019</span>
<span class="subheading" style="text-align:center; font-weight:bold; font-style: italic">
June 16, 2019, Long Beach, California.
</h2>
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Invited Speakers
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<strong>TBA</strong>
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<h2>
Workshop Program
</h2>
<p>
The <a href="https://drive.google.com/open?id=1vhQwveUtyFN4Cc5dHloumkP4x1m-1GV5">ppts</a> of talkers are available now.
</p>
<!-- <p>
TBA.
</p> -->
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<thead>
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<th width="25%">Time</th>
<th width="60%">Title</th>
<th width="15%">Speakers</th>
</tr>
</thead>
<tbody>
<tr>
<td>8:30</td>
<td>Initial remarks and workshop introduction</td>
<td>Orgnizers</td>
</tr>
<tr>
<td>8:40</td>
<td>Task1 winner talk</td>
<td>winner</td>
</tr>
<tr>
<td>9:00</td>
<td>Task2 winner talk</td>
<td>winner</td>
</tr>
<tr>
<td>9:20</td>
<td>Multi-Scale Weighted Branch Network for Remote Sensing Image Classification (Oral) </td>
<td>Paper author</td>
</tr>
<tr>
<td>9:40</td>
<td>Window Detection in Facades for Aerial Texture Files of 3D CityGML Models
</td>
<td>Paper author</td>
</tr>
<tr>
<td>10:00</td>
<td>Learning Object-Wise Semantic Representation for Detection in Remote Sensing Imagery</td>
<td></td>
</tr>
</tbody>
</table> -->
<ul>
<li>
<strong>8:40 - 8:50 Welcome, Introduction </strong>
</li>
<li>
<strong>8:50 - 9:10 Winner talk of Task1:</strong> The USTC-NELSLIP System for DOTA Contest
</li>
<li>
<strong> 9:10 - 9:30 Winner talk of Task2:</strong> Learning Object-Wise Semantic Representation for Detection in Remote Sensing Imagery
</li>
<li>
<strong> 9:30 - 9:50 Oral Presentation:</strong> Multi-Scale Weighted Branch Network for Remote Sensing Image Classification
</li>
<!-- <li>
<strong> 9:50 - 10:10 Coffee Break </strong>
</li> -->
<li>
<strong> 9:50 - 10:10 Oral Presentation:</strong> Window Detection in Facades for Aerial Texture Files of 3D CityGML Models
</li>
<li>
<strong>10:10 - 10:30 Coffee Break </strong>
</li>
<li>
<strong> 10:30 - 10:50 Oral Presentation:</strong> iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images
</li>
<li>
<strong> 10:50 - 11:10 Oral Presentation:</strong> ArcticNet: A Deep Learning Solution to Classify the Arctic Area
</li>
<li>
<strong> 11:10 - 11:30 Oral Presentation:</strong> The Aerial Elephant Dataset: A New Public Benchmark for Aerial Object Detection
</li>
<li>
<strong> 11:30 - 11:50 Oral Presentation:</strong> Multi-Cue Vehicle Detection for Semantic Video Compression in Georegistered Aerial Videos
</li>
<li>
<strong> 11:50 - 12:10 Award ceremony for the challenge winners</strong>
</li>
</ul>
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<a href="http://captain.whu.edu.cn/">CAPTAIN</a>
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