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README.md

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         <strong>GIM: Learning Generalizable Image Matcher From Internet Videos</strong>
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-    <td><a target="_blank" rel="nofollow" href="https://iclr.cc/Conferences/2024"><img style="margin: 0;" alt="ICLR 2024 Spotlight" src="https://img.shields.io/badge/%F0%9F%8C%9F_ICLR'2024_Spotlight-37414c"></a></td>
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-    <td><a target="_blank" rel="nofollow" href="https://www.youtube.com/watch?v=FU_MJLD8LeY"><img style="margin: 0;" alt="Overview Video" src="https://img.shields.io/badge/Overview_Video-E33122?logo=Youtube"></a></td>
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-<div align="center"><a href="https://www.youtube.com/watch?v=FU_MJLD8LeY"><img src="video.png" alt="Overview Video Page" style="margin: 0; width: 75%;"></a></div> 
+<div align="center"><a href="https://www.youtube.com/watch?v=FU_MJLD8LeY" target="_blank"><img src="video.png" alt="Overview Video Page" style="margin: 0; width: 75%;"></a></div> 
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         We propose GIM, a self-training framework for learning a single generalizable model based on any image matching architecture using internet videos, an abundant and diverse data source.