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<!DOCTYPE HTML>
<html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Amit Choudhari</title>
<meta name="author" content="Amit Choudhari">
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link rel="icon" href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🌐</text></svg>">
</head>
<body>
<table style="width:100%;max-width:800px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr style="padding:0px">
<td style="padding:0px">
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr style="padding:0px">
<td style="padding:2.5%;width:63%;vertical-align:middle">
<p style="text-align:center">
<name>Amit Choudhari</name>
</p>
<p>I am a master's student at <a href="https://www.polytechnique.edu/en">Ecole Polytechnique</a>, where I am Majoring in Cyber security.
</p>
<p>
In past, I worked at Qualcomm on the development of ARM TrustZone based security solutions like Secure UI and Secure Camera.
</p>
<p style="text-align:center">
<a href="mailto:[email protected]">Email</a>  / 
<a href="data/Amit-CV.pdf">CV</a>  / 
<!--<a href="data/JonBarron-bio.txt">Bio</a>  /  -->
<a href="https://scholar.google.com/citations?user=-c1sFJEAAAAJ&hl=en&oi=ao">Google Scholar</a>  / 
<a href="https://twitter.com/amit_ch0udhari">Twitter</a>  / 
<a href="https://github.com/amit-choudhari">Github</a>
</p>
</td>
<td style="padding:2.5%;width:40%;max-width:40%">
<a href="images/amit.jpg"><img style="width:100%;max-width:100%" alt="profile photo" src="images/amit_circle.png" class="hoverZoomLink"></a>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Research</heading>
<p>
I'm interested in Secure software development, side-channel security and system security in general.
</p>
</td>
</tr>
</tbody></table>
<!--
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr onmouseout="malle_stop()" onmouseover="malle_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='malle_image'>
<img src='images/MalleConv_after.jpg' width="160"></div>
<img src='images/MalleConv_before.jpg' width="160">
</div>
<script type="text/javascript">
function malle_start() {
document.getElementById('malle_image').style.opacity = "1";
}
function malle_stop() {
document.getElementById('malle_image').style.opacity = "0";
}
malle_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://yifanjiang.net/MalleConv.html">
<papertitle>Fast and High-quality Image Denoising via Malleable Convolutions</papertitle>
</a>
<br>
<a href="https://yifanjiang.net/">Yifan Jiang</a>,
<a href="https://bartwronski.com/">Bartlomiej Wronski</a>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>, <br>
<strong>Jonathan T. Barron</strong>,
<a href="https://spark.adobe.com/page/CAdrFMJ9QeI2y/">Zhangyang Wang</a>,
<a href="https://people.csail.mit.edu/tfxue/">Tianfan Xue</a>
<br>
<em>ECCV</em>, 2022
<br>
<a href="https://yifanjiang.net/MalleConv.html">project page</a>
/
<a href="https://arxiv.org/abs/2201.00392">arXiv</a>
<p></p>
<p>
We denoise images efficiently by predicting spatially-varying kernels at low resolution and using a fast fused op to jointly upsample and apply these kernels at full resolution.
</p>
</td>
</tr>
<tr onmouseout="nerfsuper_stop()" onmouseover="nerfsuper_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='nerfsuper_image'><video width=100% height=100% muted autoplay loop>
<source src="images/nerf_supervision.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/nerf_supervision.jpg' width="160">
</div>
<script type="text/javascript">
function nerfsuper_start() {
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}
nerfsuper_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="http://yenchenlin.me/nerf-supervision/">
<papertitle>NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields</papertitle>
</a>
<br>
<a href="https://yenchenlin.me/">Lin Yen-Chen</a>,
<a href="http://www.peteflorence.com/">Pete Florence</a>,
<strong>Jonathan T. Barron</strong>, <br>
<a href="https://scholar.google.com/citations?user=_BPdgV0AAAAJ&hl=en">Tsung-Yi Lin</a>,
<a href="https://meche.mit.edu/people/faculty/[email protected]">Alberto Rodriguez</a>,
<a href="http://web.mit.edu/phillipi/">Phillip Isola</a>
<br>
<em>ICRA</em>, 2022
<br>
<a href="http://yenchenlin.me/nerf-supervision/">project page</a> /
<a href="https://arxiv.org/abs/2203.01913">arXiv</a> /
<a href="https://www.youtube.com/watch?v=_zN-wVwPH1s">video</a> /
<a href="https://github.com/yenchenlin/nerf-supervision-public">code</a> /
<a href="https://colab.research.google.com/drive/13ISri5KD2XeEtsFs25hmZtKhxoDywB5y?usp=sharing">colab</a>
<p></p>
<p>NeRF works better than RGB-D cameras or multi-view stereo when learning object descriptors.</p>
</td>
</tr>
<tr onmouseout="refnerf_stop()" onmouseover="refnerf_start()" bgcolor="#ffffd0">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='refnerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/refnerf.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/refnerf.jpg' width="160">
</div>
<script type="text/javascript">
function refnerf_start() {
document.getElementById('refnerf_image').style.opacity = "1";
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refnerf_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://dorverbin.github.io/refnerf/index.html">
<papertitle>Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields</papertitle>
</a>
<br>
<a href="https://scholar.harvard.edu/dorverbin/home">Dor Verbin</a>,
<a href="https://phogzone.com/">Peter Hedman</a>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>, <br>
<a href="Todd Zickler">Todd Zickler</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>
<br>
<em>CVPR</em>, 2022   <font color="red"><strong>(Oral Presentation, Best Student Paper Honorable Mention)</strong></font>
<br>
<a href="https://dorverbin.github.io/refnerf/index.html">project page</a>
/
<a href="https://arxiv.org/abs/2112.03907">arXiv</a>
/
<a href="https://youtu.be/qrdRH9irAlk">video</a>
<p></p>
<p>Explicitly modeling reflections in NeRF produces realistic shiny surfaces and accurate surface normals, and lets you edit materials.</p>
</td>
</tr>
<tr onmouseout="mip360_stop()" onmouseover="mip360_start()" bgcolor="#ffffd0">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='mip360_image'><video width=100% height=100% muted autoplay loop>
<source src="images/mip360_sat.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/mip360_sat.jpg' width="160">
</div>
<script type="text/javascript">
function mip360_start() {
document.getElementById('mip360_image').style.opacity = "1";
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mip360_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="http://jonbarron.info/mipnerf360">
<papertitle>Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields</papertitle>
</a>
<br>
<strong>Jonathan T. Barron</strong>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<a href="https://scholar.harvard.edu/dorverbin/home">Dor Verbin</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<a href="https://phogzone.com/">Peter Hedman</a>
<br>
<em>CVPR</em>, 2022   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="http://jonbarron.info/mipnerf360">project page</a>
/
<a href="https://arxiv.org/abs/2111.12077">arXiv</a>
/
<a href="https://youtu.be/zBSH-k9GbV4">video</a>
<p></p>
<p>mip-NeRF can be extended to produce realistic results on unbounded scenes.</p>
</td>
</tr>
<tr onmouseout="rawnerf_stop()" onmouseover="rawnerf_start()" bgcolor="#ffffd0">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='rawnerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/rawnerf.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/rawnerf.jpg' width="160">
</div>
<script type="text/javascript">
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</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://bmild.github.io/rawnerf/index.html">
<papertitle>NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images</papertitle>
</a>
<br>
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<a href="https://phogzone.com/">Peter Hedman</a>,
<a href="http://www.ricardomartinbrualla.com/">Ricardo Martin-Brualla</a>, <br>
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<strong>Jonathan T. Barron</strong>
<br>
<em>CVPR</em>, 2022   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="https://bmild.github.io/rawnerf/index.html">project page</a>
/
<a href="https://arxiv.org/abs/2111.13679">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=JtBS4KBcKVc">video</a>
<p></p>
<p>
Properly training NeRF on raw camera data enables HDR view synthesis and bokeh, and outperforms multi-image denoising.</p>
</td>
</tr>
<tr onmouseout="regnerf_stop()" onmouseover="regnerf_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='regnerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/regnerf_after.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/regnerf_before.jpeg' width="160">
</div>
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</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://m-niemeyer.github.io/regnerf/index.html">
<papertitle>RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs</papertitle>
</a>
<br>
<a href="https://m-niemeyer.github.io/">Michael Niemeyer</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>, <br>
<a href="https://msmsajjadi.github.io/">Mehdi S. M. Sajjadi</a>,
<a href="http://www.cvlibs.net/">Andreas Geiger</a>,
<a href="http://www2.informatik.uni-freiburg.de/~radwann/">Noha Radwan</a>
<br>
<em>CVPR</em>, 2022   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="https://m-niemeyer.github.io/regnerf/index.html">project page</a>
/
<a href="https://arxiv.org/abs/2112.00724">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=QyyyvA4-Kwc">video</a>
<p></p>
<p>Regularizing unseen views during optimization enables view synthesis from as few as 3 input images.</p>
</td>
</tr>
<tr onmouseout="blocknerf_stop()" onmouseover="blocknerf_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='blocknerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/blocknerf_after.mp4" type="video/mp4">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://waymo.com/research/block-nerf/">
<papertitle>Block-NeRF: Scalable Large Scene Neural View Synthesis</papertitle>
</a>
<br>
<a href="http://matthewtancik.com/">Matthew Tancik</a>,
<a href="http://casser.io/">Vincent Casser</a>,
<a href="https://sites.google.com/site/skywalkeryxc/">Xinchen Yan</a>,
<a href="https://scholar.google.com/citations?user=5mJUkI4AAAAJ&hl=en">Sabeek Pradhan</a>, <br>
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://www.henrikkretzschmar.com/">Henrik Kretzschmar</a>
<br>
<em>CVPR</em>, 2022   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="https://waymo.com/research/block-nerf/">project page</a>
/
<a href="https://arxiv.org/abs/2202.05263">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=6lGMCAzBzOQ">video</a>
<p></p>
<p>We can do city-scale reconstruction by training multiple NeRFs with millions of images.</p>
</td>
</tr>
<tr onmouseout="hnerf_stop()" onmouseover="hnerf_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='hnerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/hnerf_after.mp4" type="video/mp4">
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</video></div>
<img src='images/hnerf_before.jpg' width="160">
</div>
<script type="text/javascript">
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hnerf_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://grail.cs.washington.edu/projects/humannerf/">
<papertitle>HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video</papertitle>
</a>
<br>
<a href="https://homes.cs.washington.edu/~chungyi/">Chung-Yi Weng</a>,
<a href="https://homes.cs.washington.edu/~curless/">Brian Curless</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>, <br>
<strong>Jonathan T. Barron</strong>,
<a href="https://www.irakemelmacher.com/">Ira Kemelmacher-Shlizerman </a>
<br>
<em>CVPR</em>, 2022   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="https://grail.cs.washington.edu/projects/humannerf/">project page</a>
/
<a href="https://arxiv.org/abs/2201.04127">arXiv</a>
/
<a href="https://youtu.be/GM-RoZEymmw">video</a>
<p></p>
<p>Combining NeRF with pose estimation lets you use a monocular video to do free-viewpoint rendering of a human.</p>
</td>
</tr>
<tr onmouseout="urf_stop()" onmouseover="urf_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='urf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/urf.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/urf.jpg' width="160">
</div>
<script type="text/javascript">
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}
urf_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://urban-radiance-fields.github.io/">
<papertitle>Urban Radiance Fields</papertitle>
</a>
<br>
<a href="http://www.krematas.com/">Konstantinos Rematas</a>,
<a href="https://andrewhliu.github.io/">Andrew Liu</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul P. Srinivasan</a>,
<strong>Jonathan T. Barron</strong>, <br>
<a href="https://taiya.github.io/">Andrea Tagliasacchi</a>,
<a href="https://www.cs.princeton.edu/~funk/">Tom Funkhouser</a>,
<a href="https://sites.google.com/corp/view/vittoferrari"> Vittorio Ferrari</a>
<br>
<em>CVPR</em>, 2022
<br>
<a href="https://urban-radiance-fields.github.io/">project page</a>
/
<a href="https://arxiv.org/abs/2111.14643">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=qGlq5DZT6uc">video</a>
<p></p>
<p>
Incorporating lidar and explicitly modeling the sky lets you reconstruct urban environments.</p>
</td>
</tr>
<tr onmouseout="ddp_stop()" onmouseover="ddp_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='ddp_image'>
<img src='images/ddp_after.jpg' width="160"></div>
<img src='images/ddp_before.jpg' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://arxiv.org/abs/2112.03288">
<papertitle>Dense Depth Priors for Neural Radiance Fields from Sparse Input Views</papertitle>
</a>
<br>
<a href="https://niessnerlab.org/members/barbara_roessle/profile.html">Barbara Roessle</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<a href="https://www.niessnerlab.org/">Matthias Nießner</a>
<br>
<em>CVPR</em>, 2022
<br>
<a href="https://arxiv.org/abs/2112.03288">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=zzkvvdcvksc">video</a>
<p></p>
<p>
Dense depth completion techniques applied to freely-available sparse stereo data can improve NeRF reconstructions in low-data regimes.
</p>
</td>
</tr>
<tr onmouseout="clipnerf_stop()" onmouseover="clipnerf_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='clipnerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/dreamfield_after.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/dreamfield_before.jpg' width="160">
</div>
<script type="text/javascript">
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clipnerf_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ajayj.com/dreamfields">
<papertitle>Zero-Shot Text-Guided Object Generation with Dream Fields</papertitle>
</a>
<br>
<a href="https://www.ajayj.com/">Ajay Jain</a>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://people.eecs.berkeley.edu/~pabbeel/">Pieter Abbeel</a>,
<a href="https://cs.stanford.edu/~poole/">Ben Poole</a>
<br>
<em>CVPR</em>, 2022
<br>
<a href="https://ajayj.com/dreamfields">project page</a>
/
<a href="https://arxiv.org/abs/2112.01455">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=1Fke6w46tv4">video</a>
<p></p>
<p>Supervising the CLIP embeddings of NeRF renderings lets you to generate 3D objects from text prompts.</p>
</td>
</tr>
<tr onmouseout="survey_stop()" onmouseover="survey_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='survey_image'>
<img src='images/survey_after.png' width="160"></div>
<img src='images/survey_before.png' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://arxiv.org/abs/2111.05849">
<papertitle>Advances in Neural Rendering</papertitle>
</a>
<br>
<a href="https://people.mpi-inf.mpg.de/~atewari/">Ayush Tewari</a>,
<a href="https://justusthies.github.io/">Justus Thies</a>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<a href="https://people.mpi-inf.mpg.de/~tretschk/">Edgar Tretschk</a>,
<a href="https://homes.cs.washington.edu/~yifan1/">Yifan Wang</a>,
<a href="https://christophlassner.de/">Christoph Lassner</a>,
<a href="https://vsitzmann.github.io/">Vincent Sitzmann</a>,
<a href="http://ricardomartinbrualla.com/">Ricardo Martin-Brualla</a>,
<a href="https://stephenlombardi.github.io/">Stephen Lombardi</a>,
<a href="http://www.cs.cmu.edu/~tsimon/">Tomas Simon</a>,
<a href="https://www.mpi-inf.mpg.de/departments/visual-computing-and-artificial-intelligence">Christian Theobalt</a>,
<a href="https://www.niessnerlab.org/">Matthias Niessner</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://stanford.edu/~gordonwz/">Gordon Wetzstein</a>,
<a href="https://zollhoefer.com/">Michael Zollhoefer</a>,
<a href="https://people.mpi-inf.mpg.de/~golyanik/">Vladislav Golyanik</a>
<br>
<em>Arxiv</em>, 2021
<br>
<p></p>
<p>
A survey of recent progress in neural rendering.
</p>
</td>
</tr>
<tr onmouseout="npil_stop()" onmouseover="npil_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='npil_image'>
<img src='images/npil_after.jpg' width="160"></div>
<img src='images/npil_before.jpg' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://markboss.me/publication/2021-neural-pil/">
<papertitle>Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition</papertitle>
</a>
<br>
<a href="https://markboss.me">Mark Boss</a>,
<a href="https://varunjampani.github.io">Varun Jampani</a>,
<a href="https://uni-tuebingen.de/en/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/computergrafik/lehrstuhl/mitarbeiter/raphael-braun/">Raphael Braun</a>, <br>
<a href="http://people.csail.mit.edu/celiu/">Ce Liu</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://uni-tuebingen.de/en/faculties/faculty-of-science/departments/computer-science/lehrstuehle/computergrafik/computer-graphics/staff/prof-dr-ing-hendrik-lensch/">Hendrik P. A. Lensch</a>
<br>
<em>NeurIPS</em>, 2021
<br>
<a href="https://markboss.me/publication/2021-neural-pil/">project page</a> /
<a href="https://www.youtube.com/watch?v=p5cKaNwVp4M">video</a> /
<a href="https://arxiv.org/abs/2110.14373">arXiv</a>
<p></p>
<p>
Replacing a costly illumination integral with a simple network query enables more accurate novel view-synthesis and relighting compared to NeRD.
</p>
</td>
</tr>
<tr onmouseout="hypernerf_stop()" onmouseover="hypernerf_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='hypernerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/hypernerf_after.mp4" type="video/mp4">
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</video></div>
<img src='images/hypernerf_before.jpg' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://hypernerf.github.io/">
<papertitle>HyperNeRF: A Higher-Dimensional Representation
for Topologically Varying Neural Radiance Fields</papertitle>
</a>
<br>
<a href="https://keunhong.com">Keunhong Park</a>,
<a href="https://utkarshsinha.com">Utkarsh Sinha</a>,
<a href="https://phogzone.com/">Peter Hedman</a>,
<strong>Jonathan T. Barron</strong>, <br>
<a href="http://sofienbouaziz.com">Sofien Bouaziz</a>,
<a href="https://www.danbgoldman.com">Dan B Goldman</a>,
<a href="http://www.ricardomartinbrualla.com">Ricardo Martin-Brualla</a>,
<a href="https://homes.cs.washington.edu/~seitz/">Steven M. Seitz</a>
<br>
<em>SIGGRAPH Asia</em>, 2021
<br>
<a href="https://hypernerf.github.io/">project page</a>
/
<a href="https://arxiv.org/abs/2106.13228">arXiv</a>
<p></p>
<p>Applying ideas from level set methods to NeRF lets you represent scenes that deform and change shape.</p>
</td>
</tr>
<tr onmouseout="nerfactor_stop()" onmouseover="nerfactor_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='nerfactor_image'>
<img src='images/nerfactor_after.png' width="160"></div>
<img src='images/nerfactor_before.png' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://people.csail.mit.edu/xiuming/projects/nerfactor/">
<papertitle>NeRFactor: Neural Factorization of Shape and Reflectance<br>
Under an Unknown Illumination</papertitle>
</a>
<br>
<a href="https://people.csail.mit.edu/xiuming/">Xiuming Zhang</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<a href="https://boyangdeng.com/">Boyang Deng</a>,<br>
<a href="https://www.pauldebevec.com/">Paul Debevec</a>,
<a href="http://billf.mit.edu/">William T. Freeman</a>,
<strong>Jonathan T. Barron</strong>
<br>
<em>SIGGRAPH Asia</em>, 2021
<br>
<a href="https://people.csail.mit.edu/xiuming/projects/nerfactor/">project page</a>
/
<a href="https://arxiv.org/abs/2106.01970">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=UUVSPJlwhPg">video</a>
<p></p>
<p>By placing priors on illumination and materials, we can recover NeRF-like models of the intrinsics of a scene from a single multi-image capture.</p>
</td>
<tr onmouseout="dualfont_stop()" onmouseover="dualfont_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='dualfont_image'><img src='images/dualfont_after.png'></div>
<img src='images/dualfont_before.png'>
</div>
<script type="text/javascript">
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function dualfont_stop() {
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://arxiv.org/abs/2109.06627">
<papertitle>Scalable Font Reconstruction with Dual Latent Manifolds</papertitle>
</a>
<br>
<a href="http://www.cs.cmu.edu/~asrivats/">Nikita Srivatsan</a>,
<a href="http://siwu.io/">Si Wu</a>,
<strong>Jonathan T. Barron</strong>,
<a href="http://cseweb.ucsd.edu/~tberg/">Taylor Berg-Kirkpatrick</a>
<br>
<em>EMNLP</em>, 2021
<br>
<p></p>
<p>VAEs can be used to disentangle a font's style from its content, and to generalize to characters that were never observed during training.</p>
</td>
</tr>
<tr onmouseout="mipnerf_stop()" onmouseover="mipnerf_start()" bgcolor="#ffffd0">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='mipnerf_image'><video width=100% height=100% muted autoplay loop>
<source src="images/mipnerf_ipe_yellow.mp4" type="video/mp4">
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</video></div>
<img src='images/mipnerf_ipe_yellow.png' width="160">
</div>
<script type="text/javascript">
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}
mipnerf_stop()
</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="http://jonbarron.info/mipnerf">
<papertitle>Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields</papertitle>
</a>
<br>
<strong>Jonathan T. Barron</strong>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<a href="http://matthewtancik.com/">Matthew Tancik</a>, <br>
<a href="https://phogzone.com/">Peter Hedman</a>,
<a href="http://www.ricardomartinbrualla.com/">Ricardo Martin-Brualla</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>
<br>
<em>ICCV</em>, 2021   <font color="red"><strong>(Oral Presentation, Best Paper Honorable Mention)</strong></font>
<br>
<a href="http://jonbarron.info/mipnerf">project page</a>
/
<a href="https://arxiv.org/abs/2103.13415">arXiv</a>
/
<a href="https://youtu.be/EpH175PY1A0">video</a>
/
<a href="https://github.com/google/mipnerf">code</a>
<p></p>
<p>NeRF is aliased, but we can anti-alias it by casting cones and prefiltering the positional encoding function.</p>
</td>
</tr>
<tr onmouseout="nerfbake_stop()" onmouseover="nerfbake_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='nerfbake_image'><video width=100% height=100% muted autoplay loop>
<source src="images/nerfbake_15.mp4" type="video/mp4">
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</video></div>
<img src='images/nerfbake_160.png' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="http://nerf.live">
<papertitle>Baking Neural Radiance Fields for Real-Time View Synthesis</papertitle>
</a>
<br>
<a href="https://phogzone.com/">Peter Hedman</a>,
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<a href="https://bmild.github.io/">Ben Mildenhall</a>,
<strong>Jonathan T. Barron</strong>,
<a href="https://www.pauldebevec.com/">Paul Debevec</a>
<br>
<em>ICCV</em>, 2021   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="http://nerf.live">project page</a>
/
<a href="https://arxiv.org/abs/2103.14645">arXiv</a>
/
<a href="https://www.youtube.com/watch?v=5jKry8n5YO8">video</a>
/
<a href="https://nerf.live/#demos">demo</a>
<p></p>
<p>Baking a trained NeRF into a sparse voxel grid of colors and features lets you render it in real-time in your browser.</p>
</td>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='nerfie_image'><video width=100% height=100% muted autoplay loop>
<source src="images/nerfie_after.mp4" type="video/mp4">
Your browser does not support the video tag.
</video></div>
<img src='images/nerfie_before.jpg' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://nerfies.github.io/">
<papertitle>Nerfies: Deformable Neural Radiance Fields</papertitle>
</a>
<br>
<a href="https://keunhong.com">Keunhong Park</a>,
<a href="https://utkarshsinha.com">Utkarsh Sinha</a>,
<strong>Jonathan T. Barron</strong>, <br>
<a href="http://sofienbouaziz.com">Sofien Bouaziz</a>,
<a href="https://www.danbgoldman.com">Dan B Goldman</a>,
<a href="https://homes.cs.washington.edu/~seitz/">Steven M. Seitz</a>,
<a href="http://www.ricardomartinbrualla.com">Ricardo-Martin Brualla</a>
<br>
<em>ICCV</em>, 2021   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="https://nerfies.github.io/">project page</a> /
<a href="https://arxiv.org/abs/2011.12948">arXiv</a> /
<a href="https://www.youtube.com/watch?v=MrKrnHhk8IA">video</a>
<p></p>
<p>Building deformation fields into NeRF lets you capture non-rigid subjects, like people.
</p>
</td>
</tr>
<tr onmouseout="c5_stop()" onmouseover="c5_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<div class="two" id='c5_image'>
<img src='images/c5_after.jpg' width="160"></div>
<img src='images/c5_before.jpg' width="160">
</div>
<script type="text/javascript">
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</script>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://arxiv.org/abs/2011.11890">
<papertitle>Cross-Camera Convolutional Color Constancy</papertitle>
</a>
<br>
<a href="https://sites.google.com/corp/view/mafifi">Mahmoud Afifi</a>,
<strong>Jonathan T. Barron</strong>,
<a href="http://www.chloelegendre.com/">Chloe LeGendre</a>,
<a href="https://research.google/people/105312/">Yun-Ta Tsai</a>,
<a href="https://www.linkedin.com/in/fbleibel/">Francois Bleibel</a>
<br>
<em>ICCV</em>, 2021   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<p></p>
<p>
With some extra (unlabeled) test-set images, you can build a hypernetwork that calibrates itself at test time to previously-unseen cameras.
</p>
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<a href="https://imaging.cs.cmu.edu/dual_pixels/">
<papertitle>Defocus Map Estimation and Deblurring from a Single Dual-Pixel Image</papertitle>
</a>
<br>
<a href="https://shumianxin.github.io/">Shumian Xin</a>,
<a href="http://nealwadhwa.com">Neal Wadhwa</a>,
<a href="https://people.csail.mit.edu/tfxue/">Tianfan Xue</a>,
<strong>Jonathan T. Barron</strong>, <br>
<a href="https://pratulsrinivasan.github.io/">Pratul Srinivasan</a>,
<a href="http://people.csail.mit.edu/jiawen/">Jiawen Chen</a>,
<a href="https://www.cs.cmu.edu/~igkioule/">Ioannis Gkioulekas</a>,
<a href="http://rahuldotgarg.appspot.com/">Rahul Garg</a>
<br>
<em>ICCV</em>, 2021   <font color="red"><strong>(Oral Presentation)</strong></font>
<br>
<a href="https://imaging.cs.cmu.edu/dual_pixels/">project page</a> /
<a href="https://github.com/cmu-ci-lab/dual_pixel_defocus_estimation_deblurring">code</a>
<br>
<p></p>
<p>
Multiplane images can be used to simultaneously deblur dual-pixel images, despite variable defocus due to depth variation in the scene.
</p>
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<a href="https://markboss.me/publication/2021-nerd/">
<papertitle>NeRD: Neural Reflectance Decomposition from Image Collections</papertitle>
</a>
<br>
<a href="https://markboss.me">Mark Boss</a>,
<a href="https://uni-tuebingen.de/en/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/computergrafik/lehrstuhl/mitarbeiter/raphael-braun/">Raphael Braun</a>,