logo

app.vue

@@ -1,10 +1,10 @@
 <script setup>
 useHead({
-  title: 'MeDM: Mediating Image Diffusion Models for Video-to-Video Translation with Temporal Correspondence Guidance',
+  title: 'Diffusion-based Aesthetic QR Code Generation via Scanning-Robust Perceptual Guidance',
   meta: [
     {
       name: 'description',
-      content: 'MeDM utilizes pre-trained image Diffusion Models for video-to-video translation with consistent temporal flow. The proposed framework can render videos from scene position information, such as a normal G-buffer, or perform text-guided editing on videos captured in real-world scenarios. We employ explicit optical flows to construct a practical coding that enforces physical constraints on generated frames and mediates independent frame-wise scores. By leveraging this coding, maintaining temporal consistency in the generated videos can be framed as an optimization problem with a closed-form solution. To ensure compatibility with Stable Diffusion, we also suggest a workaround for modifying observed-space scores in latent-space Diffusion Models. Notably, MeDM does not require fine-tuning or test-time optimization of the Diffusion Models.',
+      content: 'Diffusion-based Aesthetic QR Code Generation via Scanning-Robust Perceptual Guidance',
     },
     {
       name: "google-site-verification",
@@ -14,11 +14,11 @@ useHead({
 })
 
 useSeoMeta({
-  title: 'MeDM: Mediating Image Diffusion Models for Video-to-Video Translation with Temporal Correspondence Guidance',
-  ogTitle: 'MeDM: Mediating Image Diffusion Models for Video-to-Video Translation with Temporal Correspondence Guidance',
-  description: 'MeDM utilizes pre-trained image Diffusion Models for video-to-video translation with consistent temporal flow. The proposed framework can render videos from scene position information, such as a normal G-buffer, or perform text-guided editing on videos captured in real-world scenarios. We employ explicit optical flows to construct a practical coding that enforces physical constraints on generated frames and mediates independent frame-wise scores. By leveraging this coding, maintaining temporal consistency in the generated videos can be framed as an optimization problem with a closed-form solution. To ensure compatibility with Stable Diffusion, we also suggest a workaround for modifying observed-space scores in latent-space Diffusion Models. Notably, MeDM does not require fine-tuning or test-time optimization of the Diffusion Models.',
-  ogDescription: 'MeDM utilizes pre-trained image Diffusion Models for video-to-video translation with consistent temporal flow. The proposed framework can render videos from scene position information, such as a normal G-buffer, or perform text-guided editing on videos captured in real-world scenarios. We employ explicit optical flows to construct a practical coding that enforces physical constraints on generated frames and mediates independent frame-wise scores. By leveraging this coding, maintaining temporal consistency in the generated videos can be framed as an optimization problem with a closed-form solution. To ensure compatibility with Stable Diffusion, we also suggest a workaround for modifying observed-space scores in latent-space Diffusion Models. Notably, MeDM does not require fine-tuning or test-time optimization of the Diffusion Models.',
-  ogImage: 'https://medm2023.github.io/images/system-diagram.jpg',
+  title: 'Diffusion-based Aesthetic QR Code Generation via Scanning-Robust Perceptual Guidance',
+  ogTitle: 'Diffusion-based Aesthetic QR Code Generation via Scanning-Robust Perceptual Guidance',
+  description: 'Diffusion-based Aesthetic QR Code Generation via Scanning-Robust Perceptual Guidance',
+  ogDescription: 'Diffusion-based Aesthetic QR Code Generation via Scanning-Robust Perceptual Guidance',
+  ogImage: 'Diffusion-based Aesthetic QR Code Generation via Scanning-Robust Perceptual Guidance',
   twitterCard: 'summary_large_image',
 })
 

components/Footer.vue

@@ -2,13 +2,13 @@
 <div class="footer">
   <div class="content">
     <div class="logo">
-      <img src="/images/logos/as-white.png" alt="">
+      <ImageZoom src="images/logos/as-white.png" :options="{ background: imageOverlayColor }" />
     </div>
     <div>
       This website is licensed under a Creative Commons Attribution-ShareAlike 4.0 International <a href="https://creativecommons.org/licenses/by-sa/4.0/" target="_blank">License</a>.
       <br />
       <br />
-      This means you are free to borrow the <a href="https://github.com/medm2023/medm2023.github.io" target="_blank">source code</a> of this website, we just ask that you link back to this page in the footer. However, the copyright to the logo of Academia Sinica and the footer theme is reserved. Please remove them if your are not affiliated with Academia Sinica.
+      This means you are free to borrow the <a href="https://github.com/jwliao1209/DiffQRCode" target="_blank">source code</a> of this website, we just ask that you link back to this page in the footer. However, the copyright to the logo of Academia Sinica and the footer theme is reserved. Please remove them if your are not affiliated with Academia Sinica.
     </div>
   </div>
 </div>