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<html>
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<meta name="description" content="Ekta Prashnani Homepage">
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<font face= "Century Gothic, CenturyGothic, AppleGothic, sans-serif" size="6">
Ekta Prashnani<br>
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<font face="Century Gothic, CenturyGothic, AppleGothic, sans-serif" size="4">
Research Scientist <br>
NVIDIA<br>
<!-- [<a href="https://github.com/prashnani" border="0" style="color:528B8B">GitHub</a>]
[<a href="https://scholar.google.com/citations?user=na-Ba1EAAAAJ&hl=en" border="0" style="color:528B8B">Google Scholar</a>]
[<a href="https://prashnani.github.io/indexfiles/Ekta_Prashnani_CV_NOV2022.pdf" border="0" style="color:528B8B">CV</a>]<br> -->
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<p>
<font style="font-size: 13pt;" face="Century Gothic, CenturyGothic, AppleGothic, sans-serif" style="color:528B8B" target="_blank">
I am a Research Scientist at NVIDIA Research, working on verifying trustworthy use of synthetic content (see <a href="https://youtu.be/mjuQqwDOyQE">Avatar Fingerprinting</a> for verifying the authorized use of synthetic talking-head videos at ECCV'24) and on multi-modal foundation models.
<br>
Some past notable works include <a href="https://arxiv.org/abs/2211.09363">PhaseForenics</a>, a generalizable, phase-based deepfake detector; <a href="https://arxiv.org/abs/1806.02067" style="color:528B8B" target="_blank">PieAPP</a> a perceptually-consistent image error assessment method and accompanying dataset; and
a <a href="https://arxiv.org/abs/2104.08038" style="color:528B8B" target="_blank">noise-aware training</a> approach for video saliency.
<br>
<br>
</font>
</p><hr size="1" align="left" color="c3c3c3">
<font face= "Century Gothic, CenturyGothic, AppleGothic, sans-serif" style="font-size: 22pt;"> News
<table style="font-size: 13pt;" border="0" width="100%" font size="3">
<tbody>
<tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Jul, 2024: <a href="https://research.nvidia.com/labs/nxp/avatar-fingerprinting/">Avatar Fingerprinting</a>, the first work on verifying authorized use of synthetic talking-head videos, is accepted for publication at ECCV (summary video <a href="https://youtu.be/mjuQqwDOyQE">link</a>).</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Jun, 2024: PhaseForensics (a phase-based deepfake detector) is accepted for publication at the Transactions on Image Processing: stay tuned for updates!</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Jan, 2024: <a href="https://scholar.google.com/citations?user=jJz3mXcAAAAJ&hl=en">Leonard Salewski</a> started his internship with me: an exciting start to 2024!</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Sep, 2023: Our work on Avatar Fingerprinting for verifying the authorized use of synthetic talking-head videos is now available on <a href="https://arxiv.org/abs/2305.03713">arXiv</a>.</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Nov, 2022: Our work on PhaseForensics: A generalizable deepfake detector for phase-based motion analysis is now available on <a href="https://arxiv.org/abs/2211.09363">arXiv</a>.</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Apr, 2022: Started as a Research Scientist in the Human Performance and Experience team at NVIDIA.</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Feb, 2022: Successfully defended my thesis "Data-driven Methods for Evaluating the Perceptual Quality and Authenticity of Visual Media".</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Oct, 2021: Participated in ICCV 2021 Doctoral Consortium.</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Jun, 2021: ECE Dissertation Fellowship by the ECE department at UCSB.</td></tr><tr></tr><tr></tr>
<!-- <tr><td width="100%" align="Left">Apr, 2021: Our work on noise-aware training strategies for visual saliency prediction (accepted at BMVC'21) is now available on <a href="https://arxiv.org/abs/2104.08038" style="color:528B8B" target="_blank">arXiv</a>.</td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Jan, 2021: The PieAPP dataset is now available publicly! See <a href="https://github.com/prashnani/PerceptualImageError/blob/master/dataset/dataset_README.md" style="color:528B8B" target="_blank">
here</a> for details. </td></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Jun, 2018: Our CVPR2018 paper about a new <a href="https://arxiv.org/abs/1806.02067" style="color:528B8B" target="_blank">
perceptual image-error metric (PieAPPv0.1)</a>
and the associated <a href="https://github.com/prashnani/PerceptualImageError" style="color:528B8B" target="_blank">source code and trained model</a>
is now online!</td></tr><tr></tr><tr></tr> -->
</tbody>
</table>
<hr size="1" align="left" color="c3c3c3">
<font face= "Century Gothic, CenturyGothic, AppleGothic, sans-serif" style="font-size: 22pt;"> Publications
<table style="font-size: 13pt;" border="0" width="100%" font size="3">
<tbody>
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<tr><td width="100%" align="Left">Ekta Prashnani, Koki Nagano, Shalini De Mello, David Leubke, Orazio Gallo, "Avatar Fingerprinting for Authorized Use of Synthetic Talking-Head Videos" <em> European Conference on Computer Vision, 2024.</em> <br> <center>
[<a href="https://arxiv.org/abs/2305.03713" style="color:528B8B">paper</a>]
[<a href="https://research.nvidia.com/labs/nxp/avatar-fingerprinting/">project page</a>]
[<a href="https://research.nvidia.com/labs/nxp/nvfair/">project page</a>]
[<a href="https://research.nvidia.com/labs/nxp/avatar-fingerprinting/">summary video</a>]</center>
<p><center>
<img width="60%" src="indexfiles/avatar-fingerprinting-teaser.png" border="0" ></center>
</p>
</td></tr>
<tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr>
<tr><td width="30%" align="Left">Ekta Prashnani, Michael Goebel, B. S. Manjunath, "Generalizable Deepfake Detection with Phase-Based Motion Analysis" <em> IEEE Transactions on Image Processing, 2024.</em> <br> <center>
[<a href="https://arxiv.org/abs/2211.09363" style="color:528B8B">paper</a>]
[source code (Coming soon!)]
[summary video (Coming soon!)]</center>
<p><center>
<img width="100%" src="indexfiles/phase-forensics-teaser.png" border="0" ></center>
</p>
</td></tr>
<tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Ekta Prashnani, Orazio Gallo, Joohwan Kim, Josef Spjut, Pradeep Sen, Iuri Frosio, "Noise-Aware Video Saliency Prediction," <em> British Machine Vision Conference, 2021.</em> <br> <center>
[<a href="https://arxiv.org/abs/2104.08038" style="color:528B8B">paper</a>]
[<a href="https://github.com/NVlabs/NAT-saliency" style="color:528B8B">source code</a>]
[<a href="https://github.com/NVlabs/NAT-saliency" style="color:528B8B">dataset</a>]
[<a href="https://youtu.be/KU4KTlKbH54" style="color:528B8B">summary video</a>]</center>
<p><center>
<img width="100%" src="indexfiles/NAT-overview.png" border="0" ></center>
</p>
</td></tr>
<tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Ekta Prashnani*, Herbert (Hong) Cai*, Yasamin Mostofi and Pradeep Sen, "PieAPP: Perceptual Image-Error
Assessment through Pairwise Preference," <em> Computer Vision and Pattern Recognition, 2018.</em> <br> <center>
[<a href="http://civc.ucsb.edu/graphics/Papers/CVPR2018_PieAPP/" style="color:528B8B">project webpage</a>]
[<a href="https://arxiv.org/abs/1806.02067v1" style="color:528B8B">paper</a>]
[<a href="https://openaccess.thecvf.com/content_cvpr_2018/Supplemental/3483-supp.pdf" style="color:528B8B">supplementary</a>]
[<a href="https://prashnani.github.io/indexfiles/Prashnani_CVPR_2018_PieAPP_poster.pdf" style="color:528B8B">poster</a>]
[<a href="https://github.com/prashnani/PerceptualImageError" style="color:528B8B">source code</a>]
[<a href="https://github.com/prashnani/PerceptualImageError/blob/master/dataset/dataset_README.md" style="color:528B8B">dataset</a>]
[<a href="https://www.ece.ucsb.edu/~ekta/projects/PieAPPv0.1/PieAPPv0.1_win64_exe.zip" style="color:528B8B">.exe</a>]</center>
<p><center>
<img width="100%" src="indexfiles/teaser_PieAPPv0.1.png" border="0" ></center>
</p>
</td></tr>
<tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr></tr><tr></tr><tr></tr><tr></tr><tr></tr>
<tr><td width="100%" align="Left">Ekta Prashnani, Maneli Noorkami, Daniel Vaquero and Pradeep Sen, "A Phase-Based Approach for Animating Images Using Video Examples," <em> Computer Graphics Forum, August 2016, Volume 36,
Issue 6.</em>
<center>[<a href="http://onlinelibrary.wiley.com/doi/10.1111/cgf.12940/abstract" style="color:528B8B" target="_blank">paper</a>]
[<a href="https://youtu.be/qaItuwdh1Rw" style="color:528B8B" target="_blank">video results</a>] </center>
</td></tr>
<tr></tr>
<tr></tr>
<tr><td width="100%" align="Left"><small>*joint first authors</td></tr>
</tbody>
</table>
<!-- <hr size="1" align="left" color="c3c3c3"> -->
<!-- <font face= "Century Gothic, CenturyGothic, AppleGothic, sans-serif" style="font-size: 22pt;" id="teaching"> Teaching
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<tbody>
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<td width="40%" align="center">
<img width="80%" src="indexfiles/capstone2019.jpg" border="0" >
</td>
<td align="Left">Technical Mentorship for EE Capstone (2018-2019)<br>
<br><font style="font-size: 11pt;">Provided technical mentorship to seniors on their
EE Capstone projects (total five capstone projects).
<br>I worked very closely with the capstone team (left to right in the top picture: Benjamin Hirt, Erik Rosten, Shan-Wei Sun) working on
<a href="https://capstone.engineering.ucsb.edu/projects/arthrex-autoscribe" style="color:528B8B" target="_blank">the design and deployment of machine-learning-based
medical image recognition algorithms for arthroscopic images</a> (sponsored by Arthrex). The team used an Nvidia Jetson TX2 interfaced with the live camera feed from
an Arthrex surgical drawer, to deploy the trained deep-learning-based models. Check out a brief live demo
<a href="https://www.youtube.com/watch?time_continue=1&v=U-643GFKFdY&feature=emb_logo" style="color:528B8B" target="_blank">here</a> (starting at 25s). </font></td></tr>
</tbody>
</table>
<br>
<table style="font-size: 13pt;" border="0" width="100%" font size="3">
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<tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr>
<td width="40%" align="center">
<img width="80%" src="indexfiles/capstone_2017_2018.jpg" border="0" >
</td>
<td align="Left">Technical Mentorship for EE Capstone (2017-2018)<br>
<br><font style="font-size: 11pt;">Provided technical mentorship to seniors on their
EE Capstone projects (total five capstone projects).
<br>I worked very closely with the capstone team working on
<a href="https://capstone.engineering.ucsb.edu/projects/arthrex-arthroscout" style="color:528B8B" target="_blank">medical image recognition
for arthroscopic images</a> (sponsored by Arthrex). The team (left to right: Jonathan Huynh,
Phanitta Chomsinsap, Jacob Kurtz and Alae Amara) was selected to present their
work at the <a href="https://capstone.engineering.ucsb.edu/events/edx2018" style="color:528B8B" target="_blank">Engineering Design Expo, 2018</a>, at UCSB.</font></td></tr>
</tbody>
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<br>
<table style="font-size: 13pt;" border="0" width="100%" font size="3">
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<img width="90%" src="indexfiles/summer_mentorship_2017.png" border="0" >
</td>
<td align="Left">Research Mentor for High School Students (July 2017)<br>
<br><font style="font-size: 11pt;"> In the Summer of 2017, I had the opportunity to mentor
four exceptional high school students (left to right in first picture: Sohini Kar, Jungwoo Park, Joshua Doolan, James Wang)
as a part of the <a href="http://www.summer.ucsb.edu/pre-college/research-mentorship-program-rmp" style="color:528B8B" target="_blank">
Summer Research Mentorship Program at UCSB</a>.
<br>I spent the first few weeks of the program teaching relevant concepts of computer vision and
machine learning to these students (they followed along easily - the age for brilliance keeps getting younger!).
The students spent the latter half of the program working on the research tasks I designed for them
in applying deep learning to object detection (for Sohini and Jungwoo)
and image restoration (for Joshua and James).</font></td></tr>
</tbody>
</table>
<br>
<table style="font-size: 13pt;" border="0" width="100%" font size="3">
<tbody><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr><tr></tr>
<td width="40%" align="center">
<img width="80%" src="indexfiles/capstone_2016_2017.jpg" border="0" >
</td>
<td align="Left">Technical Mentorship for EE Capstone (2016-2017)<br>
<br><font style="font-size: 11pt;">Provided technical mentorship to seniors on their EE Capstone projects (total six capstone projects).
I worked very closely with the capstone team working on
<a href="https://capstone.engineering.ucsb.edu/projects/flir-pxtal " style="color:528B8B" target="_blank">deep-learning-based image super-resolution</a> (sponsored by Flir).
<br>The team (left to right: Julian Castro, Connor Northend, Jose Jimenez) ended
up winning the award for the Best Technical Capstone Project!</font></td></tr>
</tbody>
</table>
<br>
-->
<hr size="1" align="left" color="c3c3c3"><center>
<font style="font-size: 11pt;">
I can also be found on: <a href='https://www.linkedin.com/in/ektaprashnani/' style="color:528B8B" target="_blank">[LinkedIn]</a>
<a href='https://github.com/prashnani' style="color:528B8B" target="_blank">[Github]</a>
<a href='https://scholar.google.com/citations?user=na-Ba1EAAAAJ&hl=en' style="color:528B8B" target="_blank">[Google Scholar]</a>
<a href='https://www.flickr.com/photos/133729196@N03/' style="color:528B8B" target="_blank">[Flickr]</a>
<a href='https://twitter.com/ekta_prashnani' style="color:528B8B" target="_blank">[Twitter]</a>
</font></center>
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