From fb24d675f9d2fe35dcdae5178cc4955a2d688f9c Mon Sep 17 00:00:00 2001
From: BmZhao <bmzhao@zju.edu.cn>
Date: Fri, 31 May 2024 14:48:12 +0800
Subject: [PATCH] Update index.html

---
 gaussian-prediction/index.html | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/gaussian-prediction/index.html b/gaussian-prediction/index.html
index db86485..9394243 100644
--- a/gaussian-prediction/index.html
+++ b/gaussian-prediction/index.html
@@ -228,7 +228,7 @@ <h2 class="title is-3">Ours Method</h2>
                alt="PNeRFLoc architecture."/>
         </div>
         <p>
-          Optimization start with the initial 3D Gaussians. We then optimize the parameters of the 3D Gaussians, motion
+          Optimization starts with the initial 3D Gaussians. We then optimize the parameters of the 3D Gaussians, motion
           feature, and deformable MLP to build a Hyper-Canonical space. Next in the second stage, we first initialize the key points in the
           Hyper-Canonical space by a K-Means algorithm. Then we learn the time-independent weights for each Gaussian and deform
           the 3D Gaussian by key points motion. We employ a GCN (Graph Convolutional Network) to learn the relationships between
@@ -249,7 +249,7 @@ <h2 class="title is-3">Hyper-NeRF Dataset Prediction Results</h2>
     </div>
 
     <!-- D-NeRF video. -->
-    <div class="columns is-centered has-text-centered">
+<!--     <div class="columns is-centered has-text-centered">
       <div class="column is-four-fifths">
         <h2 class="title is-3">D-NeRF Dataset Prediction Results</h2>
           <div class="container">
@@ -274,7 +274,7 @@ <h2 class="title is-3">D-NeRF Dataset Prediction Results</h2>
               </div>
           </div>
       </div>
-    </div>
+    </div> -->
     <!-- DNeRF More Results. -->
     <div class="hero-body">
       <div class="columns is-centered has-text-centered">