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<!DOCTYPE HTML>
<html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Aditya Vora</title>
<meta name="author" content="Aditya Vora">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="google-site-verification" content="kk_oB9YWBIQJXAP8_h68BzBQgJOd0tL-dK5yfSnu5eU" />
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link rel="icon" type="image/png" href="images/seal_icon.png">
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<body>
<table style="width:100%;max-width:800px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
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<p style="text-align:center">
<name>Aditya Vora</name>
</p>
<p>I am a Ph.D student at the <a href="https://gruvi.cs.sfu.ca/">GrUVi Lab</a> of <a href="https://www.sfu.ca/computing.html"> School of Computer Science</a> at <a href="https://www.sfu.ca/">Simon Fraser University</a>, under the supervision of <a href="https://www.cs.sfu.ca/~haoz/">Prof. Richard (Hao) Zhang</a>.
</p>
<p>
Prior to that, I spent couple of years working in industry where I was mainly involved in development of computer vision and machine learning solutions for fire safety and security products. I completed my master's from <a href="https://iitgn.ac.in/">Indian Institute of Technology, Gandhinagar</a>, India where I did my thesis under the supervision of <a href="https://people.iitgn.ac.in/~shanmuga/">Prof. Shanmuganathan Raman</a>. I received my bachelor's degree in Electronics and Communications Engineering from Birla Vishwakarma Mahavidyalaya, India.
<!--At Google I've worked on <a href="https://ai.googleblog.com/2014/04/lens-blur-in-new-google-camera-app.html">Lens Blur</a>, <a href="https://ai.googleblog.com/2014/10/hdr-low-light-and-high-dynamic-range.html">HDR+</a>, <a href="https://www.google.com/get/cardboard/jump/">Jump</a>, <a href="https://ai.googleblog.com/2017/10/portrait-mode-on-pixel-2-and-pixel-2-xl.html">Portrait Mode</a>, and <a href="https://www.youtube.com/watch?v=JSnB06um5r4">Glass</a>. I did my PhD at <a href="http://www.eecs.berkeley.edu/">UC Berkeley</a>, where I was advised by <a href="http://www.cs.berkeley.edu/~malik/">Jitendra Malik</a> and funded by the <a href="http://www.nsfgrfp.org/">NSF GRFP</a>. I did my bachelors at the <a href="http://cs.toronto.edu">University of Toronto</a>.
I've received the <a href="https://www2.eecs.berkeley.edu/Students/Awards/15/">C.V. Ramamoorthy Distinguished Research Award</a> and the <a href="https://www.thecvf.com/?page_id=413#YRA">PAMI Young Researcher Award</a>.-->
</p>
<p style="text-align:center">
<a href="mailto:[email protected]">Email</a>  / 
<!-- <a href="data/aditya_vora_cv.pdf">CV</a>  /  -->
<a href="https://scholar.google.com/citations?user=0LO8tDEAAAAJ&hl=en">Google Scholar</a>  / 
<a href="https://www.linkedin.com/in/aditya-vora-b66b1a58/">LinkedIn</a>  / 
<a href="https://github.com/aditya-vora">GitHub</a>  / 
<a href="https://twitter.com/anvorain">Twitter</a>
</p>
</td>
<td style="padding:2.5%;width:40%;max-width:40%">
<a href="images/IMG_1615_3.jpg"><img style="width:100%;max-width:100%" alt="profile photo" src="images/IMG_1615_3.jpg" class="hoverZoomLink"></a>
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<heading>Research</heading>
<p>
My research interests are in 3D Computer Vision and Graphics, Geometry Processing and Deep Learning.
<!--{% comment %} I'm interested in Computer Vision/Graphics and Machine Learning in general. Most of my previous research works has mainly focused on visual perception of physical world from images. {% endcomment %}-->
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<heading>(Pr)ePrints</heading>
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<img src='images/aditya-fchd.png' width="250" height="100"></div>
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<p>
<a href="https://arxiv.org/abs/1809.08766">
<papertitle>FCHD: Fast and accurate head detection in crowded scenes</papertitle>
</a>
<br>
<strong>Aditya Vora</strong>,
Vinay Chilaka
<br>
<a href="https://arxiv.org/abs/1809.08766">arxiv</a> /
<a href="data/aditya-fchd.bib">bibtex</a> /
<a href="https://github.com/aditya-vora/FCHD-Fully-Convolutional-Head-Detector">code</a>
</p>
<p></p>
<p>
A fully convolutional single stage head detector is proposed where the anchor scales are designed by taking effective receptive field into account, hence giving better average precision especially for small heads in crowded scenes.
</p>
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<heading>Publications</heading>
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<p>
<a href="https://www.sciencedirect.com/science/article/abs/pii/S0167865518300473">
<papertitle>Iterative spectral clustering for unsupervised object localization</papertitle>
</a>
<br>
<strong>Aditya Vora</strong>,
<a href="https://people.iitgn.ac.in/~shanmuga/">Shanmuganathan Raman</a>
<br>
<em>Pattern Recognition Letters <a href="https://www.sciencedirect.com/journal/pattern-recognition-letters">
(PRL)</a>,</em> 2018
<br>
<a href="https://arxiv.org/abs/1706.09719">arxiv</a> /
<a href="data/aditya-flow-free-vos.bib">bibtex</a>
</p>
<p></p>
<p>
We propose a completely unsupervised algorithm for the same, where we try to exploit the structural differences between the foreground and the background region in an image in order to localize the object in the scene.
</p>
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<img src='images/flow-free-vos.png' width="250" height="120"></div>
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<p>
<a href="https://link.springer.com/chapter/10.1007/978-981-13-0020-2_4">
<papertitle>Flow-Free Video Object Segmentation</papertitle>
</a>
<br>
<strong>Aditya Vora</strong>,
<a href="https://people.iitgn.ac.in/~shanmuga/">Shanmuganathan Raman</a>
<br>
<em>National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics <a href="https://ncvpripg.iitmandi.ac.in/">
(NCVPRIPG)</a>,</em> 2017
<br>
<a href="https://arxiv.org/abs/1706.09544">arxiv</a> /
<a href="data/aditya-isc.bib">bibtex</a>
</p>
<p></p>
<p>
We propose an fully automatic video object segmentation algorithm where localization of object segments are obtained by performing clustering on proposals generated by a segmentation proposal network. Later, the overall temporal consistency is improved using a track and fill method.
</p>
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<heading>Patents</heading>
<p>Rajkumar Palanivel, Amit Kulkarni, Douglas Beaudet, Manjuprakash Rama Rao, Atul Laxman Katole, <strong> Aditya Narendrakumar Vora</strong>, "System and Method for identifying blockages of emergency exits in a building.", 2019 (Filed: H215009-US)</p>
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<p style="text-align:left;font-size:10px">
<span style="font-size:10px;float:right">
Layout inspired by <a href="https://jonbarron.info/" style="font-size: 10px;">Jon Barron</a>
. Thank you Jon. © 2020
</span>
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