paper14

src/app/about-event.tsx

@@ -8,12 +8,21 @@ import React from 'react';
 // {
 //   title: "Title",
 //   description: "",
-//   subTitle: "Speech/Talking Face Generation",
+//   subTitle: "",
 //   imageName : "paper12.png",
 //   paper_links :""
 // },
 const EVENT_INFO = [
 
+  
+  {
+  title: "GEA: Reconstructing Expressive 3D Gaussian Avatar from Monocular Video",
+  description: "A novel method utilizing 3D Gaussians for creating expressive 3D avatars achieves state-of-the-art performance in photorealistic novel view synthesis. It features accurate pose estimation, attention-aware networks, and an iterative re-initialization strategy for high-fidelity reconstructions and fine-grained control over body and hand poses. Project-Page Project page: \
+  https://3d-aigc.github.io/GEA/",
+  subTitle: "Gaussian/Nerf/3D Reconstruction",
+  imageName : "paper14.mp4",
+  paper_links :"https://arxiv.org/pdf/2402.16607.pdf"
+},
 
 {
   title: "PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator",