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<!DOCTYPE HTML>
<html lang="en">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Woo Kyoung Han</title>
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link href="css/bootstrap.min.css" rel="stylesheet" media="screen">
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<link rel="stylesheet" type="text/css" href="stylesheet.css">
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<style>
.container {
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width: 100%;
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border-spacing: 0px;
border-collapse: separate;
margin-right: auto;
margin-left: auto;
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vertical-align: middle;
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}
.image-content {
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.image-content img {
width: 100%;
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}
@media screen and (max-width: 768px) {
.text-content,
.image-content {
width: 100%;
max-width: 100%;
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}
.image-content {
order: 2;
display: flex;
justify-content: center;
}
.image-content img {
width: auto;
max-width: 100%;
height: auto;
max-height: 300px;
}
.responsive-row {
table-layout: auto !important;
}
.responsive-row,
.responsive-row tbody,
.responsive-row tr,
.responsive-row td {
display: block !important;
width: 100% !important;
max-width: 100% !important;
box-sizing: border-box;
}
.responsive-row td {
padding: 10px 0 !important;
text-align: left;
}
.responsive-row .one {
margin: 10px auto !important;
}
}
</style>
</head>
<body class="bg_colour">
<table border=0 class="bg_colour"
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">
<div class="container">
<div class="text-content">
<p style="text-align:left">
<name>Woo Kyoung Han</name>
</p>
<p>Hi! I'm a Ph.D. student at <a href="https://www.korea.edu/sites/en/index.do">Korea University</a>,
<a href="https://ipa.korea.ac.kr/">Image Processing Algorithm Lab</a>, advised by Prof.
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl=en">Kyong Hwan Jin</a>.
Before joining Korea University, I received my M.S. from
<a href="https://www.dgist.ac.kr/">DGIST</a> (2024) under the supervision of Prof. Kyong Hwan Jin and
Prof. Sunghoon Im.
</p>
<p>
My research focuses on <strong>compressed-domain visual computing</strong>, bridging classical codec
pipelines and modern neural representations. I develop efficient visual representation and inference
methods that exploit bitstream-level structure, including <strong>JPEG-domain neural operators</strong>,
<strong>lossless implicit neural representations</strong>, and <strong>codec-guided video
understanding</strong> for vision-language models.
</p>
<p><strong>I am currently open to work</strong> — happy to chat about research collaborations,
internships, and post-Ph.D. opportunities.</p>
<p>Feel free to send me an e-mail if you want to have a chat!<br>
<b>Contact</b>: wookyoung0727@korea.ac.kr</p>
<p style="text-align:center">
<a href="files/cv.pdf" target="_blank" style="text-decoration:none;">
<i class="ai ai-cv" style="font-size:2.5em; color:#898484; margin: 0 10px;"></i>
</a>
<a href="mailto:wookyoung0727@korea.ac.kr" style="text-decoration:none;">
<i class="fas fa-envelope" style="font-size:2.5em; color:#898484; margin: 0 10px;"></i>
</a>
<a href="https://scholar.google.com/citations?user=kieVQZwAAAAJ&hl=en" target="_blank"
style="text-decoration:none;">
<i class="ai ai-google-scholar" style="font-size:2.5em; color:#898484; margin: 0 10px;"></i>
</a>
<a href="https://www.linkedin.com/in/woo-kyoung-han-521270281/" target="_blank"
style="text-decoration:none;">
<i class="fab fa-linkedin" style="font-size:2.5em; color:#898484; margin: 0 10px;"></i>
</a>
<a href="https://github.com/WooKyoungHan" target="_blank" style="text-decoration:none;">
<i class="fab fa-github" style="font-size:2.5em; color:#898484; margin: 0 10px;"></i>
</a>
</p>
</div>
<div class="image-content">
<a href="images/wookyoung.jpeg"><img alt="profile photo" src="images/wookyoung.jpeg"
class="hoverZoomLink"></a>
</div>
</div>
<hr class="soft">
<button style="border:0px transparent; background-color: transparent;outline:none;" type="button"
class="collapsible" data-toggle="collapse" data-target="#content-research" id="research">
<heading>Publications</heading>
</button>
<div id="content-research" class="collapse in">
<table class="responsive-row"
style="width:100%;table-layout:fixed;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<video autoplay loop muted playsinline style="max-width:170px;max-height:170px;border-radius:10px;">
<source src="images/jpneo_intro.mp4" type="video/mp4">
</video>
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<papertitle>JPEG Processing Neural Operator for Backward Compatibility</papertitle>
<br>
<strong>Woo Kyoung Han<sup>*</sup></strong>,
Yongjun Lee<sup>*</sup>,
<a href="https://scholar.google.com/citations?user=0VhcJXwAAAAJ&hl=ko">Byeonghun Lee</a>,
Sang Hyun Park,
Sunghoon Im, and
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl">Kyong Hwan Jin<sup>†</sup></a>
<span style="color: rgb(117, 117, 117); font-weight: 300;">(*denotes equal contributions)</span>
<br>
<em>IEEE/CVF International Conference on Computer Vision
<strong>(<u>ICCV</u>)</strong></em>, 2025.
<br>
<a href="files/jpneo_iccv2025.pdf">Paper</a>
<p>We propose <strong>JPNeO</strong>, a neural operator framework for backward-compatible JPEG
processing that operates directly in the JPEG domain.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<video autoplay loop muted playsinline style="max-width:170px;max-height:170px;border-radius:10px;">
<source src="images/lossless_inr_intro.mp4" type="video/mp4">
</video>
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<papertitle>Towards Lossless Implicit Neural Representation via Bit Plane Decomposition</papertitle>
<br>
<strong>Woo Kyoung Han</strong>,
<a href="https://scholar.google.com/citations?user=0VhcJXwAAAAJ&hl=ko">Byeonghun Lee</a>,
<a href="https://scholar.google.com/citations?user=MRz6g3QAAAAJ&hl=ko">Hyunmin Cho</a>,
Sunghoon Im, and
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl">Kyong Hwan Jin<sup>†</sup></a>
<br>
<em>IEEE/CVF Conference on Computer Vision and Pattern Recognition
<strong>(<u>CVPR</u>)</strong></em>, 2025.
<br>
<a href="files/lossless_inr_cvpr2025.pdf">Paper</a>
<p>We introduce a bit-plane decomposition that enables <strong>lossless implicit neural
representations</strong>, allowing exact reconstruction of digital signals with continuous
networks.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<video autoplay loop muted playsinline style="max-width:170px;max-height:170px;border-radius:10px;">
<source src="images/jdec_intro.mp4" type="video/mp4">
</video>
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<papertitle>JDEC: JPEG Decoding via Enhanced Continuous Cosine Coefficients</papertitle>
<br>
<strong>Woo Kyoung Han</strong>,
Sunghoon Im,
Jaedeok Kim, and
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl">Kyong Hwan Jin<sup>†</sup></a>
<br>
<em>IEEE/CVF Conference on Computer Vision and Pattern Recognition
<strong>(<u>CVPR</u>)</strong></em>, 2024.
<br>
<a href="files/jdec_cvpr2024.pdf">Paper</a>
<p>We present <strong>JDEC</strong>, a JPEG decoding network with enhanced continuous cosine
coefficients, recovering high-fidelity images directly from compressed bitstreams.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<video autoplay loop muted playsinline style="max-width:170px;max-height:170px;border-radius:10px;">
<source src="images/abcd_intro.mp4" type="video/mp4">
</video>
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<papertitle>ABCD: Arbitrary Bitwise Coefficient for De-Quantization</papertitle>
<br>
<strong>Woo Kyoung Han</strong>,
<a href="https://scholar.google.com/citations?user=0VhcJXwAAAAJ&hl=ko">Byeonghun Lee</a>,
Sang Hyun Park, and
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl">Kyong Hwan Jin<sup>†</sup></a>
<br>
<em>IEEE/CVF Conference on Computer Vision and Pattern Recognition
<strong>(<u>CVPR</u>)</strong></em>, 2023.
<br>
<a href="files/abcd_cvpr2023.pdf">Paper</a>
<p>We propose <strong>ABCD</strong>, an arbitrary-bitwise coefficient estimation framework for
de-quantization, restoring images from heavily quantized inputs across arbitrary bit-depths.
</p>
</td>
</tr>
</tbody>
</table>
</div>
<hr class="soft">
<button style="border:0px transparent; background-color: transparent;outline:none;" type="button"
class="collapsible" data-toggle="collapse" data-target="#content-coauthored" id="coauthored">
<heading>Co-authored Publications</heading>
</button>
<div id="content-coauthored" class="collapse in">
<table class="responsive-row"
style="width:100%;table-layout:fixed;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/icml26_hopfield.png' width="170" style="border-radius:10px;">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ipa.korea.ac.kr">
<papertitle>Balancing Fidelity and Diversity in Diffusion Models via Symmetric Attention
Decomposition: Hopfield Perspective
</papertitle>
</a>
<br>
Hyunmin Cho,
<strong>Woo Kyoung Han</strong>, and
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl">Kyong Hwan Jin<sup>†</sup></a>
<br>
<em>43rd International Conference on Machine Learning <strong>(<u>ICML</u>)</strong></em>,
2026.
<br>
<a href="https://ipa.korea.ac.kr">Paper</a> / <a href="https://ipa.korea.ac.kr">Website</a>
/ <a href="https://github.com/hyeon-cho/Attention-Symmetric-Decomposition">Code</a>
<p>We characterize the pre-softmax attention matrix <strong>QK</strong> in transformers as an
associative memory matrix encoding pairwise associations between input features.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/lru_sm_sr.png' width="170" style="border-radius:10px;">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<papertitle>Linear Recurrent Unit with Semantic Modulation for Image Super-Resolution</papertitle>
<br>
Mingyu Choi,
<strong>Woo Kyoung Han</strong>,
Sunghoon Im<sup>†</sup>, and
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl">Kyong Hwan Jin<sup>†</sup></a>
<br>
<em>IEEE/CVF Conference on Computer Vision and Pattern Recognition Finding
<strong>(<u>CVPR Finding</u>)</strong></em>, 2026.
<p>We propose an LRU-based restoration network with a <strong>Semantic Modulating Unit
(SMU)</strong>, learned via sparse representation, that drives LRU modulation, spatial
categorization, and feature enhancement through external priors for single-image
super-resolution.
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/asscc.png' width="120" style="border-radius:10px;">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<papertitle>A 65nm 687.5-TOPS/W Drive Strength-based SRAM Compute-In-Memory Macro with Adaptive
Dynamic Range for Edge AI Applications</papertitle>
<br>
D. G. Choi,
J. Lee,
J. Koo,
<strong>Woo Kyoung Han</strong>,
D. Park,
J. Kung,
J. Lee, and
J. H. Yoon
<br>
<em>IEEE Asian Solid-State Circuits Conference
<strong>(<u>A-SSCC</u>)</strong></em>, 2024.
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/rewarp.png' width="170" style="border-radius:10px;">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<papertitle>Learning Residual Elastic Warps for Image Stitching under Dirichlet Boundary
Condition</papertitle>
<br>
Minsu Kim,
Yongjun Lee,
<strong>Woo Kyoung Han</strong>, and
<a href="https://scholar.google.com/citations?user=aLYNnyoAAAAJ&hl">Kyong Hwan Jin<sup>†</sup></a>
<br>
<em>IEEE/CVF Winter Conference on Applications of Computer Vision
<strong>(<u>WACV</u>)</strong></em>, 2024.
</td>
</tr>
</tbody>
</table>
</div>
<hr class="soft">
<button style="border:0px transparent; background-color: transparent;outline:none;" type="button"
class="collapsible" data-toggle="collapse" data-target="#content-education" id="education">
<heading>Education</heading>
</button>
<div id="content-education" class="collapse in">
<table border=0 class="bg_colour responsive-row"
style="padding:20px;width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td style="padding:10px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/korea_univ.png' width="120">
</div>
</td>
<td style="padding:10px;width:75%;vertical-align:top">
<papertitle style="color:gray"><big>Ph.D. in Electrical Engineering</big>
</papertitle>
<papertitle><big> | Korea University</big></papertitle>
<br>
Mar 2024 - Current
<br>
<br>
<strong>Research:</strong> Signal Processing & Multimedia
<br>
<strong>Advisor:</strong> Prof. <a href="https://ipa.korea.ac.kr/">Kyong Hwan Jin</a>
</td>
</tr>
<tr>
<td style="padding:10px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/dgist.png' width="120">
</div>
</td>
<td style="padding:10px;width:75%;vertical-align:top">
<papertitle style="color:gray"><big>M.S. in Electrical Engineering & Computer Science</big>
</papertitle>
<papertitle><big> | DGIST</big></papertitle>
<br>
Mar 2022 - Feb 2024
<br>
<br>
<strong>Advisor:</strong> Prof. <a href="https://ipa.korea.ac.kr/">Kyong Hwan Jin</a> &
Prof. Sunghoon Im
</td>
</tr>
</tbody>
</table>
</div>
<hr class="soft">
<button style="border:0px transparent; background-color: transparent;outline:none;" type="button"
class="collapsible" data-toggle="collapse" data-target="#content-award" id="award">
<heading>Awards</heading>
</button>
<div id="content-award" class="collapse in">
<table border=0 class="bg_colour"
style="padding:20px;width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td>
<ul>
<li><strong>Bronze Prize</strong>, Workshop on Image Processing and Image Understanding
(IPIU), 2025</li>
<li><strong>Best Student Paper</strong>, IEIE Summer Annual Conference, 2024</li>
<li><strong>Encouragement Prize</strong>, Workshop on Image Processing and Image Understanding
(IPIU), 2024</li>
<li><strong>Gold Prize</strong>, IEEE Seoul Section Best Students Award, 2023</li>
</ul>
</td>
</tr>
</tbody>
</table>
</div>
<hr class="soft">
<button style="border:0px transparent; background-color: transparent;outline:none;" type="button"
class="collapsible" data-toggle="collapse" data-target="#content-grants" id="grants">
<heading>Grants & Fellowships</heading>
</button>
<div id="content-grants" class="collapse in">
<table border=0 class="bg_colour"
style="padding:20px;width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr>
<td>
<ul>
<li><strong>AI SeoulTech Graduate Scholarship</strong>, Seoul Scholarship Foundation, 2025</li>
<li><strong>Ph.D. Candidate Fellowship</strong>, National Research Foundation of Korea (NRF),
2024 - 2026</li>
<li><strong>Merit-based Scholarship</strong>, Korea University, 2024</li>
</ul>
</td>
</tr>
</tbody>
</table>
</div>
<hr class="soft">
<button style="border:0px transparent; background-color: transparent;outline:none;" type="button"
class="collapsible" data-toggle="collapse" data-target="#content-project" id="project">
<heading>Projects</heading>
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<li>
<strong>Platform Development for Police Health Management</strong>,
supported by the National Police Agency of Korea, 2022 - Present
<ul>
<li>Implemented JPEG-domain processing pipelines in PyTorch / C++</li>
<li>Improved robustness under distortion scenarios (quantization, noise)</li>
<li>Developed medical image compression and restoration modules for a police health
monitoring platform</li>
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<ul>
<li style="margin-bottom: 10px;">
Lossless Implicit Neural Representation via Object Signal Quantization and Bitwise
Decomposition
<br>
<span style="color:gray; font-size:small;">Korea patent publication, 2024</span>
</li>
<li style="margin-bottom: 10px;">
Apparatus and Method of Recovering Image Using Arbitrary Bitwise Coefficient Estimation
for De-quantization
<br>
<span style="color:gray; font-size:small;">Korea patent publication, 2023</span>
</li>
<li style="margin-bottom: 10px;">
System for B-Spline Texture Coefficient Estimation and Method for Generating High-Resolution
Images Using the Same
<br>
<span style="color:gray; font-size:small;">Korea patent publication, 2023</span>
</li>
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