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      <h4 class="header center black-text">FuSta</h4>
	  <h5 class="header center black-text">Hybrid Neural Fusion for Full-frame Video Stabilization</h5>

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          <div class="author"><a href="http://www.cmlab.csie.ntu.edu.tw/~yulunliu/" target="blank">Yu-Lun Liu<sup>1</sup></a></div>
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          <div class="author"><a href="https://www.wslai.net/" target="blank">Wei-Sheng Lai<sup>2</sup></a></div>
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          <div class="author"><a href="https://faculty.ucmerced.edu/mhyang/" target="blank">Ming-Hsuan Yang<sup>2,4</sup></a></div>
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          <div class="author"><a href="https://www.csie.ntu.edu.tw/~cyy/" target="blank">Yung-Yu Chuang<sup>1</sup></a></div>
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          <div class="author"><a href="https://filebox.ece.vt.edu/~jbhuang/" target="blank">Jia-Bin Huang<sup>3</sup></a></div>
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          <div class="affiliation"><a href="https://www.ntu.edu.tw/" target="blank"><sup>1</sup>National Taiwan University</a></div>
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          <div class="affiliation"><a href="https://ai.google/research" target="blank"><sup>2</sup>Google</a></div>
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          <div class="affiliation"><a href="https://vt.edu/" target="blank"><sup>3</sup>Virginia Tech</a></div>
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          <div class="affiliation"><a href="https://www.ucmerced.edu/" target="blank"><sup>4</sup>UC Merced</a></div>
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Existing video stabilization methods either require aggressive cropping of frame boundaries or generate distortion artifacts on the stabilized frames.
In this work, we present an algorithm for full-frame video stabilization by first estimating dense warp fields.
Full-frame stabilized frames can then be synthesized by fusing warped contents from neighboring frames.
The core technical novelty lies in our learning-based hybrid-space fusion that alleviates artifacts caused by optical flow inaccuracy and fast-moving objects.
We validate the effectiveness of our method on the NUS and selfie video datasets.
Extensive experiment results demonstrate the merits of our approach over prior video stabilization methods.
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          <a href="https://arxiv.org/abs/2102.06205" target="_blank">
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          <a href="https://arxiv.org/abs/2102.06205" target="_blank">arXiv</a>
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      <p>Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, and Jia-Bin Huang, "Neural Re-rendering for Full-frame Video Stabilization", arXiv, 2020</p>

      <br>

      <div class="subtitle">Bibtex</div>
      <pre>
@inproceedings{Liu-FuSta-2021,
    author    = {Liu, Yu-Lun and Lai, Wei-Sheng and Yang, Ming-Hsuan and Chuang, Yung-Yu and Huang, Jia-Bin},
    title     = {Hybrid Neural Fusion for Full-frame Video Stabilization},
    journal   = {arXiv preprint},
    year      = {2021}
}
</pre>
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      <div class="title">References</div>
      <ul>
        <li>&bull;
          <a href="http://www.liushuaicheng.org/SIGGRAPH2013/index.htm" target="blank">Bundled Camera Paths for Video Stabilization</a>, SIGGRAPH, 2013.
        </li>
        <li>&bull;
          <a href="https://www.cc.gatech.edu/cpl/projects/videostabilization/" target="blank">Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths</a>, CVPR, 2011.
        </li>
        <li>&bull;
          <a href="https://github.com/cxjyxxme/deep-online-video-stabilization" target="blank">Deep Online Video Stabilization with Multi-Grid Warping Transformation Learning</a>, TIP, 2018.
        </li>
        <li>&bull;
          <a href="https://github.com/jinsc37/DIFRINT" target="blank">Deep Iterative Frame Interpolation for Full-frame Video Stabilization</a>, SIGGRAPH Asia, 2019.
        </li>
        <li>&bull;
          <a href="http://jiyang.fun/projects.html" target="blank">Learning Video Stabilization Using Optical Flow</a>, CVPR, 2020.
        </li>
        <li>&bull;
          <a href="http://jiyang.fun/projects.html" target="blank">Selfie Video Stabilization</a>, ECCV, 2018.
        </li>
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