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<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black">We
are excited to announce the CholecTriplet2022 challenge, a
surgical action triplet detection challenge which is </span><span
style="font-family:"Calibri",sans-serif;color:black"><span
style="font-family:"Calibri",sans-serif;color:black">part
of the Endoscopic Vision Grand challenge at MICCAI 2022</span>.
In this edition, participants are tasked with recognizing and
localizing tool-tissue interactions, represented as triplets of
<i><instrument, verb, target></i>, from laparoscopic
videos. Participants will compete to train models using only
frame-level annotations to predict the triplets present in a
given image and localize the instrument used to carry out the
action. </span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="color:black"> </span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black">This
challenge is in line with recent efforts in the computer vision
and deep learning community, which have begun to transition from
coarse-grained tasks such as action and activity recognition to
finer-grained tasks such as <i>
Human-Object Interaction (HOI)</i>. </span><span
style="font-family:"Calibri",sans-serif;color:#212529;background:white">Formalizing
surgical activities using triplets and localizing them
represents a step toward comprehensive fine-grained modeling in
the surgical domain, and can facilitate the development of
intra-operative decision support systems in the operating room
(OR). CholecTriplet2022 offers participants the opportunity to
explore these research areas, engage with the community,
compete, collaborate, and push the boundaries of surgical scene
understanding.</span></p>
<p style="margin:0in;text-align:justify;background:white"> </p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black">This
challenge will provide access to the
<i>CholecT50</i> dataset, a dataset of 50 surgical videos which
has been annotated by clinicians with 100 action triplet
classes. </span><span
style="font-family:"Calibri",sans-serif;color:black">A
baseline study </span><span style="color:black"><a
href="https://arxiv.org/abs/2007.05405"><span
style="color:black;text-decoration:none"></span><span
style="font-family:"Calibri",sans-serif;color:#005A95;text-decoration:none">[1]</span></a>
</span><span
style="font-family:"Calibri",sans-serif;color:black">provides</span><span
style="font-family:"Calibri",sans-serif;color:black">
additional background about the task and dataset.</span><span
style="font-family:"Calibri",sans-serif;color:black">
</span><span
style="font-family:"Calibri",sans-serif;color:black">The
teams with the best results will be rewarded with prizes. We
also plan a joint publication with top participants after the
challenge.</span>
</p>
<p style="margin:0in;text-align:justify;background:white"> </p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black">To
register for the challenge and for more information, please
visit the challenge website: </span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="color:black"><a
href="https://cholectriplet2022.grand-challenge.org/"><span
style="font-family:"Calibri",sans-serif;color:#1155CC">https://cholectriplet2022.grand-challenge.org/</span></a></span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black"> </span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black">Please
feel free to contact us at the email below should you have any
questions. We look forward to your participation!</span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black"> </span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black">Best
regards,</span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:#212529">The
CholecTriplet2022 Organizers.</span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:#212529">Aditya
Murali, Chinedu Nwoye, Saurav Sharma, Tong Yu, Armine
Vardazaryan, Deepak Alapatt, Nicolas Padoy</span></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Segoe UI
Emoji",sans-serif;color:#134F5C">✉</span><span
style="font-family:"Calibri",sans-serif;color:#134F5C">
Contact us:
</span><u><span
style="font-family:"Calibri",sans-serif;color:#005A95"><a class="moz-txt-link-abbreviated" href="mailto:cholectriplet2022-support@icube.unistra.fr">cholectriplet2022-support@icube.unistra.fr</a></span></u></p>
<p style="margin:0in;text-align:justify;background:white"><span
style="font-family:"Calibri",sans-serif;color:black"> </span></p>
<p style="margin:0in;line-height:200%"><span
style="font-size:9.0pt;line-height:200%;font-family:"Arial",sans-serif;color:#4472C4">[1]</span><span
style="font-size:10.0pt;line-height:200%;color:#4472C4"><a
href="https://arxiv.org/abs/2109.03223"><span
style="font-size:9.0pt;line-height:200%;font-family:"Arial",sans-serif;color:#4472C4;background:white">Nwoye,
C. I., Yu, T., Gonzalez, C., Seeliger, B., Mascagni, P.,
Mutter, D., ... & Padoy, N. (2022). Rendezvous:
attention mechanisms for the recognition of surgical action
triplets in endoscopic videos. Medical Image Analysis,
102433.</span></a></span></p>
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