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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<!-- Meta tags for social media banners, these should be filled in appropriatly as they are your "business card" -->
<!-- Replace the content tag with appropriate information -->
<meta name="description" content="DESCRIPTION META TAG">
<meta property="og:title" content="SOCIAL MEDIA TITLE TAG" />
<meta property="og:description" content="SOCIAL MEDIA DESCRIPTION TAG TAG" />
<meta property="og:url" content="URL OF THE WEBSITE" />
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<!-- Keywords for your paper to be indexed by-->
<meta name="keywords" content="urban, streetscapes, high-altitude">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Constellation Dataset: Benchmarking High-Altitude Object Detection for an Urban Intersection</title>
<link rel="icon" type="image/x-icon" href="static/images/favicon.ico">
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<body>
<section class="hero">
<div class="hero-body">
<div class="container is-max-desktop">
<div class="columns is-centered">
<div class="column has-text-centered">
<h1 class="title is-1 publication-title">Constellation: Benchmarking High-Altitude Object Detection for an
Urban Intersection</h1>
<div class="is-size-5 publication-authors">
<!-- Paper authors -->
<span class="author-block">
<a href="https://keremturkcan.com/" target="_blank">Mehmet Kerem Turkcan</a>,</span>
<span class="author-block">
<a href="https://www.linkedin.com/in/sanjeevnarasimhan" target="_blank">Sanjeev Narasimhan</a>,</span>
<span class="author-block"><a href="https://www.linkedin.com/in/chengbozang" target="_blank">Chengbo
Zang</a>,</span>
<span class="author-block"><a href="https://www.linkedin.com/in/jay-je/" target="_blank">Gyung Hyun
Je</a>,</span>
<span class="author-block"><a href="https://www.linkedin.com/in/bo-yu-cu/" target="_blank">Bo
Yu</a>,</span>
<span class="author-block"><a
href="https://wimnet.ee.columbia.edu/people/current-members/mahshid-ghasemi/" target="_blank">Mahshid
Ghasemi</a>,</span>
<span class="author-block"><a href="https://www.ee.columbia.edu/~jghaderi/" target="_blank">Javad
Ghaderi</a>,</span>
<span class="author-block"><a href="https://wimnet.ee.columbia.edu/people/gil-zussman/"
target="_blank">Gil Zussman</a>,</span>
<span class="author-block"><a href="https://www.aidl.ee.columbia.edu/" target="_blank">Zoran
Kostic</a></span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block">Columbia University<br>2023</span>
</div>
<div class="column has-text-centered">
<div class="publication-links">
<!-- Arxiv PDF link -->
<span class="link-block">
<a href="https://arxiv.org/abs/2404.16944" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fas fa-file-pdf"></i>
</span>
<span>Paper</span>
</a>
</span>
<!-- Github link -->
<span class="link-block">
<a href="https://github.com/zk2172-columbia/constellation-dataset" target="_blank"
class="external-link button is-normal is-rounded is-dark">
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<i class="fab fa-github"></i>
</span>
<span>Code</span>
</a>
</span><br>
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class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fas fa-database"></i>
</span>
<span>Dataset</span>
</a>
</span>
<!-- Github link -->
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<a href="https://github.com/mkturkcan/constellation?tab=readme-ov-file#model-table" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fas fa-code-branch"></i>
</span>
<span>Models</span>
</a>
</span>
</div>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- Teaser video-->
<section class="hero teaser">
<div class="container is-max-desktop">
<div class="hero-body">
<video poster="" id="tree" autoplay controls muted loop height="100%">
<!-- Your video here -->
<source src="static/videos/base2.mp4" type="video/mp4">
</video>
<h2 class="subtitle has-text-centered">
We introduce Constellation, a dataset of 13K images suitable for research on detection of objects in dense
urban streetscapes observed from high-elevation cameras, collected for a variety of temporal conditions. The
dataset addresses the need for curated data to explore problems in small object detection exemplified by the
limited pixel footprint of pedestrians observed tens of meters from above. It enables the testing of object
detection models for variations in lighting, building shadows, weather, and scene dynamics.
</h2>
</div>
</div>
</section>
<!-- End teaser video -->
<!-- Paper abstract -->
<section class="section hero is-light">
<div class="container is-max-desktop">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
We evaluate contemporary object detection architectures on the dataset, observing that state-of-the-art
methods have lower performance in detecting small pedestrians compared to vehicles, corresponding to a 10%
difference in average precision (AP). Using structurally similar datasets for pretraining the models
results in an increase of 1.8% mean AP (mAP). We further find that incorporating domain-specific data
augmentations helps improve model performance. Using pseudo-labeled data, obtained from inference outcomes
of the best-performing models, improves the performance of the models. Finally, comparing the models
trained using the data collected in two different time intervals, we find a performance drift in models
due to the changes in intersection conditions over time.
</p>
</div>
</div>
</div>
</div>
</section>
<!-- End paper abstract -->
<!-- Image carousel -->
<section class="hero is-small">
<div class="hero-body">
<div class="container">
<div id="results-carousel" class="carousel results-carousel">
<div class="item">
<!-- Your image here -->
<img src="static/images/constellation_a2.png"
alt="Constellation contains different scenes, with changing time-of-day, weather conditions and background elements." />
<h2 class="subtitle has-text-centered">
Constellation contains different scenes, with changing time-of-day, weather conditions and background
elements for the same
camera. (a-d) Different weather and time-of-day conditions; (e-h) changes to the scene background.
</h2>
</div>
<div class="item">
<!-- Your image here -->
<img src="static/images/constellation2.png" alt="Example annotated frame from Constellation." />
<h2 class="subtitle has-text-centered">
Training curves for extra-large (left) vs. nano (right) YOLOv8 models with different pretraining datasets.
</h2>
</div>
</div>
</div>
</div>
</section>
<!-- End image carousel -->
<!-- Paper poster -->
<section class="hero is-small is-light">
<div class="hero-body">
<div class="container">
<h2 class="title">Poster</h2>
<iframe src="static/pdfs/constellation.pdf" width="100%" height="550">
</iframe>
</div>
</div>
</section>
<!--End paper poster -->
<!--BibTex citation -->
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@inproceedings{Turkcan2024Constellation,
author = {Turkcan, Mehmet Kerem and Zang, Chengbo and Narasimhan, Sanjeev and Je, Gyung Hyun and Yu, Bo and Ghasemi, Mahshid and Zussman, Gil and Ghaderi, Javad and Kostic, Zoran},
title = {Constellation: Benchmarking High-Altitude Object Detection for an Urban Intersection},
booktitle = {In Preparation},
year = {2024},
note = {In Preparation},
}</code></pre>
</div>
</section>
<!--End BibTex citation -->
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