FakeReasoning/index.html at master · PRIS-CV/FakeReasoning · GitHub

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<!DOCTYPE html>
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<head>
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  <meta name="description"
    content="Discover the FakeReasoning, an accurate and interpretable AI-generated images detector.">
  <meta property="og:title" content="FakeReasoning: Towards Generalizable Forgery Detection and Reasoning">
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  <title>FakeReasoning</title>

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      <h1>Towards Generalizable Forgery Detection and Reasoning</h1>
      <p data-aos-delay="200">
        Achieving accurate and interpretable AI-generated images detection via MLLMs' visual reasoning capability.
      </p>
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          Code
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  </section>

  <!-- Abstract and Authors Section -->
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          <h2 class="subtitle is-size-5">Authors</h2>
          <div class="is-size-5 publication-authors">
            <span class="author-block">Yueying Gao<sup>1</sup>,</span>
            <span class="author-block">Dongliang Chang<sup>1</sup>,</span>
            <span class="author-block">Bingyao Yu<sup>2</sup>,</span>
            <span class="author-block">Haotian Qin<sup>1</sup>,</span>
            <span class="author-block">Muxi Diao<sup>1</sup>,</span>
            <span class="author-block">Lei Chen<sup>2</sup>,</span>
            <span class="author-block">Kongming Liang<sup>1</sup>,</span>
            <span class="author-block">Zhanyu Ma<sup>1</sup></span>
          </div>
        </div>
        <div class="is-size-5 publication-authors">
          <span class="author-block"><sup>1</sup> PRIS, Beijing University of Posts and Telecommunications</span><br>
          <span class="author-block"><sup>2</sup> Tsinghua University</span><br>
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  </section>

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          <h2 class="title is-3" style="text-align: center;">Contributions</h2>
          <div class="content has-text-left">
            <div class="bullet-point">
              <strong>FakeReasoning:</strong> A forgery detection and reasoning framework, providing accurate detection
              with structured and reliable reasoning over forgery attributes.
            </div>
            <div class="bullet-point">
              <strong>MMFR-Dataset:</strong> A multi-modal forgery reasoning dataset, containing 120K training images
              and 20K evaluation images annotated with detailed reasoning over forgery attributes.
            </div>
          </div>
        </div>
      </div>
    </div>
  </section>

  <!-- Visualization Section -->
  <section class="py-5">
    <div class="tab-container">
      <h2 class="mb-4 text-center">Detection and Reasoning Performance of FakeReasoning</h2>
      <p class="mb-4">
        <strong>FakeReasoning</strong> conducts forgery reasoning task
        in structured stages (summary, caption, reasoning and conclusion) and hierarchical steps (low-level and high-level),
        leading to accurate and interpretable detection.
      </p>
      <div class="tab-nav">
        <button class="tab-button active" onclick="switchTab(event, 'tab1')">GAN-generated image</button>
        <button class="tab-button" onclick="switchTab(event, 'tab2')">DM-generated image</button>
        <button class="tab-button" onclick="switchTab(event, 'tab3')">Real image I</button>
        <button class="tab-button" onclick="switchTab(event, 'tab4')">Real image II</button>
      </div>

      <div id="tab1" class="tab-content active">
        <img src="static/images/visualization_1.png" alt="GAN-generated image" style="max-width: 100%; height: auto;">
      </object>
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        <img src="static/images/visualization_2.png" alt="DM-generated image" style="max-width: 100%; height: auto;">
      </div>

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        <img src="static/images/visualization_3.png" alt="Real image I" style="max-width: 100%; height: auto;">
      </div>

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        <img src="static/images/visualization_4.png" alt="Real image II" style="max-width: 100%; height: auto;">
      </div>
    </div>
  </section>

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      <h2 class="mb-4" >MMFR-Dataset</h2>
      <p class="mb-4">
        Constructed with advanced GPT-4o, <strong>MMFR-Dataset</strong> contains over 100,000 images with over
        310,000 reasoning annotations as its training set. <br>
        Here we illustrate several images and according annotations from reasoning stage.
      </p>

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          <div class="carousel-item active">
            <img loading="lazy" src="static/images/train_1.jpg" class="responsive-image" alt="Image 1">
          </div>
          <div class="carousel-item">
            <img loading="lazy" src="static/images/train_2.jpg" class="responsive-image" alt="Image 2">
          </div>
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      <p class="mb-4">
        Evaluation sets include 20,000 images with over 66,000 reasoning annotations across 10 up-to-data generative models
        and are balanced in terms of authenticity.<br>
        Here we illustrate several real and fake images from each evaluation set.
      </p>

      <div id="mmfrEvaluationCarousel" class="carousel slide"  data-bs-interval="false">
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          <div class="carousel-item active">
            <h4 class="text-center">GPT-4o</h4>
            <img loading="lazy" src="static/images/GPT-4o.png" class="responsive-image" alt="Evaluation Image 1">
          </div>
          <div class="carousel-item">
            <h4 class="text-center">FLUX</h4>
            <img loading="lazy" src="static/images/FLUX.png" class="responsive-image" alt="Evaluation Image 2">
          </div>
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            <h4 class="text-center">PixArt-α</h4>
            <img loading="lazy" src="static/images/PixArt-α.png" class="responsive-image" alt="Evaluation Image 3">
          </div>
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            <h4 class="text-center">Kandinsky</h4>
            <img loading="lazy" src="static/images/Kandinsky.png" class="responsive-image" alt="Evaluation Image 4">
          </div>
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            <h4 class="text-center">Midjourney</h4>
            <img loading="lazy" src="static/images/Midjourney.png" class="responsive-image" alt="Evaluation Image 5">
          </div>
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            <h4 class="text-center">DeepFloyd IF</h4>
            <img loading="lazy" src="static/images/DeepFloyd_IF.png" class="responsive-image" alt="Evaluation Image 6">
          </div>
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            <h4 class="text-center">DALLE-3</h4>
            <img loading="lazy" src="static/images/DALLE-3.png" class="responsive-image" alt="Evaluation Image 7">
          </div>
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            <h4 class="text-center">Stable Diffusion</h4>
            <img loading="lazy" src="static/images/Stable_Diffusion.png" class="responsive-image" alt="Evaluation Image 8">
          </div>
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            <h4 class="text-center">GigaGAN</h4>
            <img loading="lazy" src="static/images/GigaGAN.png" class="responsive-image" alt="Evaluation Image 9">
          </div>
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            <h4 class="text-center">StyleGAN-XL</h4>
            <img loading="lazy" src="static/images/StyleGAN-XL.png" class="responsive-image" alt="Evaluation Image 10">
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                <pre class="m-0" style="font-family: 'Roboto Mono', monospace; font-size: 0.9rem; color: #2d3748;">
@article{gao2025fakereasoning,
  title={FakeReasoning: Towards Generalizable Forgery Detection and Reasoning},
  author={Gao, Yueying and Chang, Dongliang and Yu, Bingyao and Qin, Haotian and Chen, Lei and Liang, Kongming and Ma, Zhanyu},
  journal={arXiv preprint arXiv:2503.21210},
  year={2025},
  url={https://arxiv.org/abs/2503.21210}
}
</pre>
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