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<title>Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches</title>
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<table align=center width=600px>
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</td>
</tr>
</table>
<!-- <center><span style="font-size:44px;font-weight:bold;"></span></center><br/> -->
<center><span style="font-size:44px;font-weight:bold;">Doodle It Yourself:</span>
</center>
<center><span style="font-size:32px;font-weight:bold;">Class Incremental Learning by Drawing a Few Sketches</span>
</center><br />
<table align=center width=1200px>
<tr>
<td align=center width=270px>
<center><span style="font-size:22px"><a href="http://ayankumarbhunia.github.io/" target="_blank">Ayan
Kumar Bhunia</a></span></center>
</td>
<td align=center width=230px>
<center><span style="font-size:22px"><a
href="https://scholar.google.com/citations?user=9C5TEbkAAAAJ&hl=en/"
target="_blank">Viswanatha Reddy</a></span></center>
</td>
<td align=center width=200px>
<center><span style="font-size:22px"><a href="https://subhadeepkoley.github.io/"
target="_blank">Subhadeep Koley</a></span></center>
</td>
<td align=center width=150px>
<center><span style="font-size:22px"><a href="https://rohit-kundu.github.io//" target="_blank">Rohit
Kundu</a></span></center>
</td>
<br>
<td align=center width=150px>
<center><span style="font-size:22px"><a href="https://aneeshan95.github.io/" target="_blank">Aneeshan
Sain</a></span></center>
</td>
<td align=center width=130px>
<center><span style="font-size:22px"><a
href="http://personal.ee.surrey.ac.uk/Personal/T.Xiang/index.html/" target="_blank">Tao
Xiang</a></span></center>
</td>
<td align=center width=180px>
<center><span style="font-size:22px"><a href="http://personal.ee.surrey.ac.uk/Personal/Y.Song/"
target="_blank">Yi-Zhe Song</a></span></center>
</td>
<tr />
<!-- <tr>-->
<!-- <td align=center width=250px>-->
<!-- <center><span style="font-size:20px">SketchX, CVSSP, University of Surrey, United Kingdom</span></center></td>-->
<!-- <td align=center width=250px>-->
<!-- <center><span style="font-size:20px">CMU</span></center></td>-->
<!-- <td align=center width=150px>-->
<!-- <center><span style="font-size:20px">CMU/FAIR</span></center></td>-->
<!-- <td align=center width=150px>-->
<!-- <center><span style="font-size:20px">UIUC</span></center></td>-->
<!-- <tr/>-->
<!-- </table>-->
<table align=center width=1000px>
<tr>
<td align=center width=800px>
<center><span style="font-size:22px">SketchX, Centre for Vision Speech and Signal Processing,
<br /> University of Surrey, United Kingdom </span></center>
</td>
<tr />
</table><br />
<table align=center width=700px>
<tr>
<td align=center width=700px>
<center><span style="font-size:22px">Published at <a href="http://cvpr2022.thecvf.com/">CVPR
2022</a> </span></center>
</td>
<tr />
</table><br />
<table align=center width=700px>
<tr>
<td align=center width=70px>
<center><span style="font-size:28px"><a
href="https://arxiv.org/pdf/2203.14843.pdf">[Paper]</a></span></center>
</td>
<!-- <td align=center width=70px><center><span style="font-size:28px"><a href="https://www.youtube.com/watch?v=JVyFexPEu-U">[Talk]</a></span></center></td> -->
<!-- <td align=center width=70px><center><span style="font-size:28px"><a href="https://github.com/AyanKumarBhunia/on-the-fly-FGSBIR/blob/master/images/4367-talk.pdf">[Slides]</a></span></center></td> -->
<td align=center width=100px>
<center><span style="font-size:28px"><a
href="https://github.com/AyanKumarBhunia/DIY-FSCIL">[GitHub]</a></span>
</center>
</td>
<!-- <td align=center width=100px><center><span style="font-size:28px"><a href='https://github.com/devendrachaplot/Neural-SLAM'>[GitHub Code]</a></span></center></td>-->
<tr />
</table><br />
<!-- <center><h2>Project Video</h2></center> -->
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<tr>
<td align=center width=600px>
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<center><img src="./sample_images/first.PNG" height="300px"></img><br></center>
</td>
</tr>
</table>
<br>
<div style="width:800px; margin:0 auto; text-align=justify">
llustration of our DIY-FSCIL framework. For instance,
given sketch exemplars (1-shot here) from 3 novel classes as
support-set, a 10-class classifier gets updated to (10 + 3)-class
classifier that can classify photos from both base and novel classes</div>
<br>
<hr>
<center>
<h1>Framework</h1>
</center>
<div style="width:800px; margin:0 auto; text-align=justify">
The human visual system is remarkable in learning new visual concepts from just a few examples. This is
precisely the goal behind few-shot class incremental learning (FSCIL), where the emphasis is
additionally placed on ensuring the model does not suffer from "forgetting". In this paper, we push the
boundary further for FSCIL by addressing two key questions that bottleneck its ubiquitous application
(i) can the model learn from diverse modalities other than just photo (as humans do), and (ii) what if
photos are not readily accessible (due to ethical and privacy constraints). Our key innovation lies in
advocating the use of sketches as a new modality for class support. The product is a "Doodle It
Yourself" (DIY) FSCIL framework where the users can freely sketch a few examples of a novel class for
the model to learn to recognize photos of that class. For that, we present a framework that infuses (i)
gradient consensus for domain invariant learning, (ii) knowledge distillation for preserving old class
information, and (iii) graph attention networks for message passing between old and novel classes. We
experimentally show that sketches are better class support than text in the context of FSCIL, echoing
findings elsewhere in the sketching literature.
</div><br />
<table align=center width=1000px>
<p style="margin-top:4px;"></p>
<tr>
<td width=1200px>
<center><a href="./sample_images/second.PNG"><img src="./sample_images/second.PNG"
width="800px"></img></a><br>
</center>
</td>
</tr>
</table>
<br />
<hr>
<!--https://youtu.be/JVyFexPEu-U-->
<table align=center width=850px>
<center>
<h1>Bibtex</h1>
</center>
<tr>
<td width=200px align=left>
<!-- <p style="margin-top:4px;"></p> -->
<!-- <a href="https://arxiv.org/pdf/2002.10310.pdf"><img style="width:200px" src="./images/4367-teaser.gif"/></a> -->
<center>
<!-- <span style="font-size:20pt"><a href="https://arxiv.org/pdf/2002.10310.pdf">[Paper]</a> -->
<!-- <span style="font-size:20pt"><a href="https://arxiv.org/abs/1902.05546v2">[ArXiv]</a>-->
<!-- <span style="font-size:20pt"><a href="resources/slides.pdf">[Slides]</a></span>-->
<!-- <span style="font-size:20pt"><a href="resources/poster.pdf">[Poster]</a></span>-->
</center>
</td>
<td width=50px align=center>
</td>
<td width=550px align=left>
<!-- <p style="margin-top:4px;"></p> -->
<!-- Chaplot, D.S., Gandhi, D., Gupta, S., Gupta, A. and Salakhutdinov, R., 2020. Learning To Explore Using Active Neural SLAM. In International Conference on Learning Representations (ICLR).-->
<p style="text-align:left;"><b><span style="font-size:20pt">Citation</span></b><br /><span
style="font-size:6px;"> <br /></span> <span style="font-size:15pt"> Doodle It
Yourself: Class Incremental Learning by Drawing a Few Sketches. In
CVPR 2022.</span></p>
<!-- <p style="margin-top:20px;"></p> -->
<span style="font-size:20pt"><a shape="rect" href="javascript:togglebib('assemblies19_bib')"
class="togglebib">[Bibtex]</a></span>
<div class="paper" id="assemblies19_bib">
<pre xml:space="preserve">
@InProceedings{DoodleIncremental,
author = {Ayan Kumar Bhunia and Viswanatha Reddy Gajjala and Subhadeep Koley and Rohit Kundu and Aneeshan Sain and Tao Xiang and Yi-Zhe Song},
title = {Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2022}
}
</pre>
</div>
</td>
</tr>
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</td>
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</td>
<td width=550px align=left>
</td>
</tr>
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<div style="width:800px; margin:0 auto; text-align=justify">
</div><br/>
<table align=center width=1000px>
<p style="margin-top:4px;"></p>
<tr><td width=1200px>
<center><a href="./images/4367-teaser.gif"><img src = "./images/4367-teaser.gif" width="512px"></img></a><br></center>
</td></tr>
</table>
<br/><hr>
<table align=center width=800px>
<tr><td width=800px><left> -->
<!-- <center><h1>Acknowledgements</h1></center>
<br>
Website template from <a href="https://richzhang.github.io/colorization">here</a> and <a href="https://pathak22.github.io/modular-assemblies/">here</a>. <br>
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