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          <h1 class="title is-3.5 publication-title">From Sim-to-Real: Toward General Event-based Low-light Frame Interpolation with Per-scene Optimization</h1>
          <div class="is-size-5 publication-authors">
            <span class="author-block">
              <a href="https://naturezhanghn.github.io">Ziran Zhang</a><sup>1,2,*</sup>,</span>
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              <a href="https://scholar.google.com/citations?user=JwQLEocAAAAJ&hl=en">Yongrui Ma</a><sup>3,2,*</sup>,</span>
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              <a href="https://scholar.google.com/citations?user=gS-0tfAAAAAJ&hl=en">Yueting Chen</a><sup>1</sup>,
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              Feng Zhang</a><sup>2</sup>,
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              <a href="https://www.gujinwei.org">Jinwei Gu</a><sup>3</sup>,
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              <a href="https://tianfan.info">Tianfan Xue</a><sup>3,†</sup>,
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              <a href="https://guoshi28.github.io">Shi Guo</a><sup>2,†</sup>
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            <span class="author-block"><sup>1</sup>Zhejiang University,</span>
            <span class="author-block"><sup>2</sup>Shanghai AI Laboratory,</span>
            <span class="author-block"><sup>3</sup>The Chinese University of Hong Kong</span>
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          <p class="author-note">*Authors contributed equally. †Corresponding authors.</p>

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        <span class="dnerf">The interpolated result</span> from the real-captured RGB-event sequence under low light conditions. Our proposed per-scene optimization method can successfully correct the impact of event latency, accurately interpolate the correct positions, and produce visually pleasing interpolation results.
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            Video Frame Interpolation (VFI) is important for video enhancement, frame rate up-conversion, and slow-motion generation. The introduction of event cameras, which capture per-pixel brightness changes asynchronously, has significantly enhanced VFI capabilities, particularly for high-speed, nonlinear motions. However, these event-based methods encounter challenges in low-light conditions, notably trailing artifacts and signal latency, which hinder their direct applicability and generalization. Addressing these issues, we propose a novel per-scene optimization strategy tailored for low-light conditions.
            This approach utilizes the internal statistics of a sequence to handle degraded event data under low-light conditions, improving the generalizability to different lighting and camera settings. To evaluate its robustness in low-light condition, we further introduce EVFI-LL, a unique RGB+Event dataset captured under low-light conditions. Our results demonstrate state-of-the-art performance in low-light environments. Both the dataset and the source code will be made publicly available upon publication.
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    <pre><code>@article{zhang2024sim,
  title={From Sim-to-Real: Toward General Event-based Low-light Frame Interpolation with Per-scene Optimization},
  author={Zhang, Ziran and Ma, Yongrui and Chen, Yueting and Zhang, Feng and Gu, Jinwei and Xue, Tianfan and Guo, Shi},
  journal={arXiv preprint arXiv:2406.08090},
  year={2024}
}</code></pre>
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