From f18046ff587946e225d112625893289a5968c928 Mon Sep 17 00:00:00 2001
From: loggerJK <jiwon7258@gmail.com>
Date: Fri, 15 Mar 2024 00:27:45 +0900
Subject: [PATCH] fix : typo

---
 index.html | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/index.html b/index.html
index fc15c85..59c735a 100755
--- a/index.html
+++ b/index.html
@@ -155,8 +155,8 @@ <h2>
             </div>
             <div style="text-align:justify;  margin-left:100px; margin-right:100px">
             3D Gaussian splatting (3DGS) has recently demonstrated
-            impressive capabilities in real-time novel view synthesis and 3D recon-
-            struction. However, 3DGS heavily depends on the accurate initialization
+            impressive capabilities in real-time novel view synthesis and 3D reconstruction.
+            However, 3DGS heavily depends on the accurate initialization
             derived from Structure-from-Motion (SfM) methods. When trained with
             randomly initialized point clouds, 3DGS often fails to maintain its ability
             to produce high-quality images, undergoing large performance drops
@@ -164,8 +164,8 @@ <h2>
             in the frequency domain and analysis of a 1D regression task
             with multiple 1D Gaussians, we propose a novel optimization strategy
             dubbed <strong>RAIN-GS</strong> (<strong>R</strong>elaxing <strong>A</strong>ccurate <strong>IN</strong>itialization Constraint for
-            3D Gaussian Splatting) that successfully trains 3D Gaussians from ran-
-            domly initialized point clouds. We show the effectiveness of our strategy
+            3D Gaussian Splatting) that successfully trains 3D Gaussians from randomly
+            initialized point clouds. We show the effectiveness of our strategy
             through quantitative and qualitative comparisons on standard datasets,
             largely improving the performance in all settings.
             </div>