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	<title>MCL</title>
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	<link>https://mcl.korea.ac.kr</link>
	<description>Media Communications Lab.</description>
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		<title>2027학년도 전기 대학원생 모집</title>
		<link>https://mcl.korea.ac.kr/2027%ed%95%99%eb%85%84%eb%8f%84-%ec%a0%84%ea%b8%b0-%eb%8c%80%ed%95%99%ec%9b%90%ec%83%9d-%eb%aa%a8%ec%a7%91/</link>
		<comments>https://mcl.korea.ac.kr/2027%ed%95%99%eb%85%84%eb%8f%84-%ec%a0%84%ea%b8%b0-%eb%8c%80%ed%95%99%ec%9b%90%ec%83%9d-%eb%aa%a8%ec%a7%91/#comments</comments>
		<pubDate>Fri, 10 Jul 2026 02:40:30 +0000</pubDate>
		<dc:creator>Chang-Su Kim</dc:creator>
				<category><![CDATA[News]]></category>

		<guid isPermaLink="false">http://mcl.korea.ac.kr/?p=44966</guid>
		<description><![CDATA[고려대학교 MCL은 compact representation, order learning 등 인공지능과 기계학습의 근간이 되는 representation learning 분야에서 새로운 연구 주제를 개척하고 있습니다. 그동안 CVPR, NeurIPS, ICLR, ICML, ICCV, ECCV 등 인공지능 및 컴퓨터 비전 분야의 최고 학술대회에 다수의 논문을 발표하며, 국내에서도 세계 최고 [...]]]></description>
			<content:encoded><![CDATA[<p>고려대학교 MCL은 compact representation, order learning 등 인공지능과 기계학습의 근간이 되는 representation learning 분야에서 새로운 연구 주제를 개척하고 있습니다. 그동안 CVPR, NeurIPS, ICLR, ICML, ICCV, ECCV 등 인공지능 및 컴퓨터 비전 분야의 최고 학술대회에 다수의 논문을 발표하며, 국내에서도 세계 최고 수준의 연구가 가능하다는 것을 꾸준히 증명해 왔습니다.</p>
<p>MCL이 지향하는 것은 이미 많은 연구자가 뛰어든 문제를 뒤따라가는 연구가 아닙니다. 아직 충분히 탐구되지 않은 중요한 문제에 도전하고, 남들이 가지 않은 길에서 새로운 방법론을 제시하는 선도 연구입니다. 연구실의 체계적인 지도와 구성원 간의 협업을 바탕으로 이러한 연구를 수행하면서, 새로운 문제를 바라보는 안목과 연구자로서의 진정한 실력을 기르게 됩니다.</p>
<p>AI, Machine Learning, Computer Vision 분야에서 세계적인 연구자로 성장하고 싶은 학생, 남을 따라가기보다 새로운 연구 흐름을 함께 개척하고자 하는 학생을 찾습니다.</p>
<p>2027년 3월 입학 예정인 석사과정, 석·박사통합과정 및 박사과정 지원에 관심 있는 분은 김창수 교수(changsukim@korea.ac.kr)에게 연락하시기 바랍니다.</p>
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		<title>[ICML2026] Order learning papers.</title>
		<link>https://mcl.korea.ac.kr/icml2026-order-learning-papers/</link>
		<comments>https://mcl.korea.ac.kr/icml2026-order-learning-papers/#comments</comments>
		<pubDate>Fri, 01 May 2026 05:20:40 +0000</pubDate>
		<dc:creator>Chang-Su Kim</dc:creator>
				<category><![CDATA[News]]></category>
		<category><![CDATA[미분류]]></category>

		<guid isPermaLink="false">http://mcl.korea.ac.kr/?p=44495</guid>
		<description><![CDATA[We are glad to announce that two order learning papers (ConOrd and SOL) will be presented at ICML 2026 in Seoul, Korea this July. Starting from the world-first order learning paper at ICLR 2020, our lab has been developing a [...]]]></description>
			<content:encoded><![CDATA[<p>We are glad to announce that two order learning papers (ConOrd and SOL) will be presented at ICML 2026 in Seoul, Korea this July. Starting from the world-first order learning paper at ICLR 2020, our lab has been developing a series of order learning techniques over the past six years.</p>
<ol>
<li value="1"> 1. Chaewon Lee, BeomJun Shim, Kwang Pyo Choi, and Chang-Su Kim, &#8220;Contrastive order learning: A general framework for ordinal regression,&#8221; ICML 2026. (<strong>ConOrd</strong>)</li>
<li value="2"> 2. Chaewon Lee, Seon-Ho Lee, and Chang-Su Kim, &#8220;Stochastic order learning: an approach to rank estimation using noisy data,&#8221; ICML 2026. (<strong>SOL</strong>)</li>
<li value="3"> 3. Nyeong-Ho Shin, Seon-Ho Lee, and Chang-Su Kim, &#8220;Blind image quality assessment based on geometric order learning,&#8221; CVPR 2024. (<strong>GOL-based BIQA</strong>)</li>
<li value="4"> 4. Seon-Ho Lee, Nyeong-Ho Shin, and Chang-Su Kim, &#8220;Unsupervised order learning,&#8221; ICLR 2024. (<strong>UOL</strong>)</li>
<li value="5"> 5. Seon-Ho Lee, Nyeong Ho Shin, and Chang-Su Kim, &#8220;Geometric order learning for rank estimation,&#8221; NeurIPS 2022. (<strong>GOL</strong>)</li>
<li value="6"> 6. Nyeong Ho Shin, Seon-Ho Lee, and Chang-Su Kim, &#8220;Moving window regression: A novel approach to ordinal regression,&#8221; CVPR 2022. (<strong>MWR</strong>)</li>
<li value="7"> 7. Seon-Ho Lee and Chang-Su Kim, &#8220;Order learning using partially ordered data via chainization,&#8221; ECCV 2022. (<strong>Chainization</strong>)</li>
<li value="8"> 8. Seon-Ho Lee and Chang-Su Kim, &#8220;Deep repulsive clustering of ordered data based on order-identity decomposition,&#8221; ICLR 2021. (<strong>DRC-ORID</strong>)</li>
<li value="9"> 9. Kyungsun Lim, Nyeong-Ho Shin, Young-Yoon Lee, and Chang-Su Kim, &#8220;Order learning and its application to age estimation,&#8221; ICLR 2020. (<strong>OL</strong>)</li>
</ol>
<p>Congratulations to Chaewon and all the authors! Following MCL tradition, the <strong>ConOrd</strong> paper might have been named <strong>COL</strong> — but Chaewon apparently had no intention of following it, and named it ConOrd instead. We think it sounds great anyway. Next up: <strong>VOL</strong>!</p>
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		<item>
		<title>[CVPR2026] Obfuscation, Color Grading, and Age Estimation</title>
		<link>https://mcl.korea.ac.kr/cvpr2026-obfuscation-color-grading-and-age-estimation/</link>
		<comments>https://mcl.korea.ac.kr/cvpr2026-obfuscation-color-grading-and-age-estimation/#comments</comments>
		<pubDate>Mon, 23 Feb 2026 06:50:26 +0000</pubDate>
		<dc:creator>Chang-Su Kim</dc:creator>
				<category><![CDATA[News]]></category>

		<guid isPermaLink="false">http://mcl.korea.ac.kr/?p=43836</guid>
		<description><![CDATA[We are pleased to announce that our group will present two main-track papers and one Findings paper at CVPR 2026, to be held in Denver, Colorado, in June 2026. Jintae Kim, Keunsoo Ko, Chang-Su Kim, Frequency-domain Manipulation for Face Obfuscation [...]]]></description>
			<content:encoded><![CDATA[<p data-start="36" data-end="195">We are pleased to announce that our group will present two main-track papers and one Findings paper at CVPR 2026, to be held in Denver, Colorado, in June 2026.</p>
<ul data-start="197" data-end="540">
<li data-start="197" data-end="291">
<p data-start="199" data-end="291">Jintae Kim, Keunsoo Ko, Chang-Su Kim, <em data-start="237" data-end="289">Frequency-domain Manipulation for Face Obfuscation </em>(Highlight)</p>
</li>
<li data-start="292" data-end="409">
<p data-start="294" data-end="409">Jinwon Ko, Keunsoo Ko, Chang-Su Kim, <em data-start="331" data-end="407">CanonCGT: Reference-Based Color Grading via Canonical Pivot Representation</em></p>
</li>
<li data-start="410" data-end="540">
<p data-start="412" data-end="540">Chaewon Lee, Jun-Hyeok Heo, Chang-Su Kim, <em data-start="454" data-end="529">GATE: Gaussian-Attentive Transformer for Uncertainty-Aware Age Estimation</em> (Findings)</p>
</li>
</ul>
<p data-start="542" data-end="607">Congratulations to all authors on these outstanding achievements.</p>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>[2025] 2026년 대학원생 모집</title>
		<link>https://mcl.korea.ac.kr/2025-2026%eb%85%84-%ec%9e%85%ed%95%99-%ec%98%88%ec%a0%95-%eb%8c%80%ed%95%99%ec%9b%90%ec%83%9d-%eb%aa%a8%ec%a7%91/</link>
		<comments>https://mcl.korea.ac.kr/2025-2026%eb%85%84-%ec%9e%85%ed%95%99-%ec%98%88%ec%a0%95-%eb%8c%80%ed%95%99%ec%9b%90%ec%83%9d-%eb%aa%a8%ec%a7%91/#comments</comments>
		<pubDate>Thu, 04 Sep 2025 01:02:21 +0000</pubDate>
		<dc:creator>Chang-Su Kim</dc:creator>
				<category><![CDATA[News]]></category>

		<guid isPermaLink="false">http://mcl.korea.ac.kr/?p=41094</guid>
		<description><![CDATA[MCL에서는 AI, Machine Learning, Computer Vision을 연구할 대학원생(2026년 3월 입학 예정)을 모집합니다. 관심 있는 학생은 김창수 교수(changsukim@korea.ac.kr)에게 연락 바랍니다.]]></description>
			<content:encoded><![CDATA[<p>MCL에서는 AI, Machine Learning, Computer Vision을 연구할 대학원생(2026년 3월 입학 예정)을 모집합니다. 관심 있는 학생은 김창수 교수(changsukim@korea.ac.kr)에게 연락 바랍니다.</p>
]]></content:encoded>
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		<slash:comments>0</slash:comments>
		</item>
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		<title>[2025] 여름방학 인턴 모집</title>
		<link>https://mcl.korea.ac.kr/2025-%ec%97%ac%eb%a6%84%eb%b0%a9%ed%95%99-%ec%9d%b8%ed%84%b4-%eb%aa%a8%ec%a7%91/</link>
		<comments>https://mcl.korea.ac.kr/2025-%ec%97%ac%eb%a6%84%eb%b0%a9%ed%95%99-%ec%9d%b8%ed%84%b4-%eb%aa%a8%ec%a7%91/#comments</comments>
		<pubDate>Thu, 29 May 2025 06:30:25 +0000</pubDate>
		<dc:creator>admin</dc:creator>
				<category><![CDATA[News]]></category>

		<guid isPermaLink="false">http://mcl.korea.ac.kr/?p=39113</guid>
		<description><![CDATA[MCL에서 컴퓨터비전, 머신러닝, 인공지능에 관심있는 인턴을 모집합니다. Lecture course, Full-time internship 두 가지 코스로 진행하며, 아래 첨부파일 확인하여 자세한 내용 확인하여 주시기 바랍니다. Lecture course는 장재석 연구원님 (jsjang@mcl.korea.ac.kr)에게, Full-time internship은 김창수 교수님 (changsukim@korea.ac.kr)에게 문의 바랍니다. MCL Summer Internship 2025 &#8211; [...]]]></description>
			<content:encoded><![CDATA[<p>MCL에서 컴퓨터비전, 머신러닝, 인공지능에 관심있는 인턴을 모집합니다.</p>
<p>Lecture course, Full-time internship 두 가지 코스로 진행하며, 아래 첨부파일 확인하여 자세한 내용 확인하여 주시기 바랍니다.</p>
<p>Lecture course는 장재석 연구원님 (jsjang@mcl.korea.ac.kr)에게,<br />
Full-time internship은 김창수 교수님 (changsukim@korea.ac.kr)에게 문의 바랍니다.</p>
<p><a href='http://mcl.korea.ac.kr/wp-content/uploads/2025/05/MCL_Internship_2025_summer_lecture.pdf'>MCL Summer Internship 2025 &#8211; Lecture course</a><br />
<a href='http://mcl.korea.ac.kr/wp-content/uploads/2025/05/MCL_Internship_2025_summer_fulltime_v2.pdf'>MCL Summer Internship 2025 &#8211; Full-time internship</a></p>
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