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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="description"
content="Towards a Generalized Multi-Modal Foundation Model">
<meta name="keywords" content="Nerfies, D-NeRF, NeRF">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Towards a Generalized Multi-Modal Foundation Model</title>
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</head>
<body>
<section class="hero">
<div class="hero-body">
<div class="container is-max-desktop">
<div class="columns is-centered">
<div class="column has-text-centered">
<!-- <h1 class="title is-1 publication-title">X-Decoder:</h1> -->
<h2 class="title is-2 publication-title">Towards a Generalized Multimodal Foundation Model</h2>
<br>
<div class="is-size-5 publication-authors">
Along the track of <a href="https://openaccess.thecvf.com/content/CVPR2023/papers/Zou_Generalized_Decoding_for_Pixel_Image_and_Language_CVPR_2023_paper.pdf"><b>X-Decoder</b></a>, <a href="https://arxiv.org/pdf/2304.06718.pdf"><b>SEEM</b></a>, and <a href="http://arxiv.org/abs/2312.07532"><b>FIND</b></a>, our goal is to build a foundation model that extendable to a wide range of vision and vision-language tasks without any overhead!
<!-- <span class="author-block"><b style="color:#f68946; font-weight:normal">▶ </b> University of Wisconsin-Madison; </b></span>
<span class="author-block"><b style="color:#F2A900; font-weight:normal">▶ </b>UCLA; </span>
<span class="author-block"><b style="color:#00A4EF; font-weight:normal">▶ </b>Microsoft Research, Redmond; </span>
<span class="author-block"><b style="color:#008AD7; font-weight:normal">▶ </b>Microsoft Cloud & AI </span> -->
</div>
<br>
<br>
<div class="columns">
<div class="column is-4" style="display: flex; flex-direction: column; border-right: 1px solid #ccc; padding-right: 20px;">
<div style="margin-bottom: 20px;">
<h2 class="subtitle" style="font-weight: bold;">
X-Decoder <span style="font-weight: normal; font-size: 14px; color: red;">(CVPR 2023)</span>
</h2>
<p>
<b>"Generalized Decoding for Pixel, Image, and Language"</b> [1] shortened as X-Decoder is a generalized decoding system that is applicable to various vision-language tasks with a unified architecture. The input and output modalities spans vision-language while the granularity spans pixel-image.
</p>
</div>
<span class="link-block">
<a href="https://github.com/microsoft/X-Decoder/tree/main" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-github"></i>
</span>
<span>Code ☆ 1.1k</span>
</a>
</span>
<span class="link-block">
<a href="https://github.com/microsoft/X-Decoder/tree/xgpt"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-hotjar"></i>
</span>
<span>X-GPT</span>
</a>
</span>
<img id="x-decoder-teaser" style="align-self: flex-start;" width="100%" src="./images/xdecoder-t.png">
</div>
<div class="column is-4" style="display: flex; flex-direction: column; border-left: 1px solid #ccc; border-right: 1px solid #ccc; padding-left: 20px; padding-right: 20px;">
<div style="margin-bottom: 20px;">
<h2 class="subtitle" style="font-weight: bold;">
SEEM <span style="font-weight: normal; font-size: 14px; color: red;">(NeurIPS 2023)</span>
</h2>
<p>
<b>"Segment Everything Everywhere All-at-Once"</b> [2] denoted as SEEM in extending X-Decoder with human interaction capability, where human can refer a segment with scribble, box, point, and etc. Meanwhile, it accepts prompts span vision-language in a composite manner.
</p>
</div>
<span class="link-block">
<a href="https://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-github"></i>
</span>
<span>Code ☆ 3.6k</span>
</a>
</span>
<span class="link-block">
<a href="http://semantic-sam.xyzou.net:6090/"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="far fa-laugh-beam"></i>
</span>
<span>Demo</span>
</a>
</span>
<img id="seem-teaser" style="align-self: flex-start;" width="100%" src="./images/seem-t.png">
</div>
<div class="column is-4" style="display: flex; flex-direction: column; border-left: 1px solid #ccc; padding-left: 20px;">
<div style="margin-bottom: 20px;">
<h2 class="subtitle" style="font-weight: bold;">
FIND <span style="font-weight: normal; font-size: 14px; color: red;">(New!)</span>
</h2>
<p>
"Interfacing Foundation Models' Embeddings" denoted as FIND introduces a generalized interface for foundation models. It aligns an embedding space with interleaved reasoning capability for pretrained-and-fixed foundation models (e.g. X-Decoder, UniCL, SAM, LLaMA).
</p>
</div>
<span>
<a href="https://github.com/UX-Decoder/FIND" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-github"></i>
</span>
<span>Code</span>
</a>
</span>
<span class="link-block">
<a href=""
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="far fa-laugh-beam"></i>
</span>
<span>Demo</span>
</a>
</span>
<img id="find-teaser" style="align-self: flex-start;" width="100%" src="./images/find-t.png">
</div>
</div>
<!-- <div class="is-size-5">
<span class="author-block">
<a href="https://maureenzou.github.io/" style="color:#f68946;font-weight:normal;">Xueyan Zou<sup>*</sup>
</a>,
</span>
<span class="author-block">
<a href="https://zdou0830.github.io/" style="color:#F2A900;font-weight:normal;">Zi-Yi Dou<sup>*</sup></a>,</span>
<span class="author-block">
<a href="https://jwyang.github.io/" style="color:#00A4EF;font-weight:normal;">Jianwei Yang<sup>*⚑</sup></a>,
</span>
<span class="author-block">
<a href="https://zhegan27.github.io/" style="color:#008AD7;font-weight:normal;">Zhe Gan</a>,
</span>
<span class="author-block">
<a href="https://www.microsoft.com/en-us/research/people/linjli/" style="color:#008AD7;font-weight:normal;">Linjie Li</a>,
</span>
<span class="author-block">
<a href="https://chunyuan.li/" style="color:#00A4EF;font-weight:normal;">Chunyuan Li</a>,
</span>
<span class="author-block">
<a href="https://sites.google.com/site/xiyangdai/" style="color:#008AD7;font-weight:normal;">Xiyang Dai</a>,
</span>
<span class="author-block">
<a href="https://harkiratbehl.github.io/" style="color:#00A4EF;font-weight:normal;">Harkirat Behl</a>,
</span>
<span class="author-block">
<a href="https://scholar.google.com/citations?user=vJWEw_8AAAAJ&hl=en" style="color:#008AD7;font-weight:normal;">Jianfeng Wang</a>,
</span>
<span class="author-block">
<a href="https://www.microsoft.com/en-us/research/people/luyuan/" style="color:#008AD7;font-weight:normal;">Lu Yuan</a>,
</span>
<span class="author-block">
<a href="https://vnpeng.net/" style="color:#F2A900;font-weight:normal;">Nanyun Peng</a>,
</span>
<span class="author-block">
<a href="https://www.microsoft.com/en-us/research/people/lijuanw/" style="color:#008AD7;font-weight:normal;">Lijuan Wang</a>,
</span>
<span class="author-block">
<a href="https://pages.cs.wisc.edu/~yongjaelee/" style="color:#f68946;font-weight:normal;">Yong Jae Lee<sup>☨</sup></a>,
</span>
<span class="author-block">
<a href="https://www.microsoft.com/en-us/research/people/jfgao/" style="color:#00A4EF;font-weight:normal;">Jianfeng Gao<sup>☨</sup></a>
</span>
</div>
<br>
<div class="is-size-5 publication-authors">
<span class="author-block"><b style="color:#f68946; font-weight:normal">▶ </b> University of Wisconsin-Madison; </b></span>
<span class="author-block"><b style="color:#F2A900; font-weight:normal">▶ </b>UCLA; </span>
<span class="author-block"><b style="color:#00A4EF; font-weight:normal">▶ </b>Microsoft Research, Redmond; </span>
<span class="author-block"><b style="color:#008AD7; font-weight:normal">▶ </b>Microsoft Cloud & AI </span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>*</sup>Equal Technical Contribution, </span>
<span class="author-block"><sup>☨</sup>Equal Advisory Contribution, </span>
<span class="author-block"><sup>⚑</sup>Project Lead </span>
</div>
<br>
<div class="is-size-5 publication-authors">
<span class="author-block"><b style="color:#e08ba0; font-weight:normal"> <b>In CVPR2023</b> </b></span>
</div> -->
</div>
</div>
</div>
</div>
</section>
<section class="hero teaser">
<div class="container is-max-desktop">
<div class="hero-body">
<b><span style="font-size: 20px; color:#ea7e56;">▶ FIND</span></b>
<img id="teaser" width="120%" src="images/find-gif.gif">
<h2 class="subtitle has-text-centered">
<p style="font-family:Times New Roman"><b>FIND interfacing foundation models for an interleaved embedding space. </b></p>
</h2>
</div>
</div>
</section>
<section class="hero teaser">
<div class="container is-max-desktop">
<div class="hero-body">
<b><span style="font-size: 20px; color:#ea7e56;">▶ SEEM</span></b>
<img id="teaser" width="120%" src="images/seem_gif.gif">
<h2 class="subtitle has-text-centered">
<p style="font-family:Times New Roman"><b>SEEM supports a wide range of prompt types including text, scribble, ref-image, and etc. </b></p>
</h2>
</div>
</div>
</section>
<section class="hero teaser">
<div class="container is-max-desktop">
<div class="hero-body">
<b><span style="font-size: 20px; color:#ea7e56;">▶ X-Deocder</span></b>
<img id="teaser" width="120%" src="images/tittle_fig.gif">
<h2 class="subtitle has-text-centered">
<p style="font-family:Times New Roman"><b>X-Decoder is a single model trained to support a wide range of vision and vision-language tasks.</b></p>
</h2>
</div>
</div>
</section>
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>
@article{zou2023xdecoder,
author = {Xueyan Zou*, Zi-Yi Dou*, Jianwei Yang*, Zhe Gan, Linjie Li, Chunyuan Li, Xiyang Dai, Harkirat Behl, Jianfeng Wang, Lu Yuan, Nanyun Peng, Lijuan Wang, Yong Jae Lee*, Jianfeng Gao*},
title = {Generalized Decoding for Pixel, Image and Language},
publisher = {CVPR},
year = {2023},
}
@article{zou2023seem,
author = {Xueyan Zou*, Jianwei Yang*, Hao Zhang*, Feng Li*, Linjie Li, Jianfeng Wang, Lijuan Wang, Jianfeng Gao*, Yong Jae Lee*},
title = {Segment everything everywhere all at once},
publisher = {NeurIPS},
year = {2023},
}
@article{zou2023find,
author = {Xueyan Zou, Linjie Li, Jianfeng Wang, Jianwei Yang, Mingyu Ding, Zhengyuan Yang, Feng Li, Hao Zhang, Shilong Liu, Arul Aravinthan, Yong Jae Lee*, Lijuan Wang*},
title = {Generalized Decoding for Pixel, Image and Language},
publisher = {arXiv},
year = {2023},
}
</code></pre>
</div>
</section>
<section class="section" id="Acknowledgement">
<div class="container is-max-desktop content">
<h2 class="title">Acknowledgement</h2>
<p>
This website is adapted from <a
href="https://github.com/nerfies/nerfies.github.io">Nerfies</a>, licensed under a <a rel="license"
href="http://creativecommons.org/licenses/by-sa/4.0/">Creative
Commons Attribution-ShareAlike 4.0 International License</a>.
</p>
</div>
</section>
</body>
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