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  <title>Ziyi Li</title>

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                <name> Ziyi Li </name>
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              <p>I am a master student working on open-world representation learning and image super-resolution at <a href="https://mediabrain.sjtu.edu.cn/">Shanghai Jiao Tong University</a>.
		      I received my bachelor degree from <a href='https://www.sjtu.edu.cn/'> Shanghai Jiao Tong University (SJTU)</a> in June 2021.
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		      My current research interest is in open-world representation learning.
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              <p style="text-align:center">
                <a href="599lzy@sjtu.edu.cn">Email</a> &nbsp/&nbsp
                <a href="https://github.com/Lipurple">Github</a>
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              <a href="image/lzy.jpg"><img style="width:100%;max-width:100%" alt="profile photo" src="image/liziyi.jpg" class="hoverZoomLink"></a>
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          <heading><b></bold>Research</b></heading>

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              <a href="https://lipurple.github.io/Grounded_Diffusion/">
                <papertitle>Guiding Text-to-Image Diffusion Model Towards Grounded Generation</papertitle>
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              <br>
              <strong>Ziyi Li* </strong>,
              <a>Qinye Zhou* </a>,
              <a href="https://cmic.sjtu.edu.cn/CN/show.aspx?info_lb=35&info_id=1341&flag=35">Xiaoyun Zhang </a>,
              <a href="https://mediabrain.sjtu.edu.cn/yazhang/">Ya Zhang </a>,
              <a href="https://mediabrain.sjtu.edu.cn/members/">Yanfeng Wang </a>,
              <a href="https://weidixie.github.io/">Weidi Xie </a>
              <br>
		    <em> International Conference on Computer Vision (ICCV)</em>, 2023
              <!-- <em>arXiv</em>, 2023 (under review) -->
              <p>we propose to augment a pre-trained text-to-image diffusion model with the ability of open-vocabulary objects grounding, i.e., simultaneously generating images and segmentation masks for the corresponding visual entities described in the text prompt.
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              <a href="https://lipurple.github.io/ARIS_Webpage//">
                <papertitle>A Simple Plugin for Transforming Images to Arbitrary Scales</papertitle>
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              <a>Qinye Zhou* </a>,
              <strong>Ziyi Li* </strong>,
              <a href="https://weidixie.github.io/">Weidi Xie </a>,
              <a href="https://cmic.sjtu.edu.cn/CN/show.aspx?info_lb=35&info_id=1341&flag=35">Xiaoyun Zhang </a>,
	      <a href="https://mediabrain.sjtu.edu.cn/members/">Yanfeng Wang </a>,
	      <a href="https://mediabrain.sjtu.edu.cn/yazhang/">Ya Zhang</a>
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			<em> British Machine Vision Conference (BMVC)</em>, 2022
              <p>we propose to develop a general <strong>plugin</strong> that can be inserted into existing super-resolution models, conveniently augmenting their ability towards <strong>A</strong>rbitrary <strong>R</strong>esolution <strong>I</strong>mage <strong>S</strong>caling, thus termed <strong>ARIS</strong>.</p>
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		Based on a template by <a href="https://github.com/jonbarron/jonbarron_website">Jon Barron</a>.
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