From a6b069e3c9ec673f06471a0b0d3e1b0ca9d7db50 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ruilong=20Li=28=E6=9D=8E=E7=91=9E=E9=BE=99=29?=
 <ruilongli94@gmail.com>
Date: Tue, 18 Jun 2024 09:59:13 -0700
Subject: [PATCH] update readme video

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 README.md | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index a5fc5f75..5d41fb79 100644
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 gsplat is an open-source library for CUDA accelerated rasterization of gaussians with python bindings. It is inspired by the SIGGRAPH paper [3D Gaussian Splatting for Real-Time Rendering of Radiance Fields](https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/), but we’ve made gsplat even faster, more memory efficient, and with a growing list of new features! 
 
 <div align="center">
-  <video src="https://github.com/nerfstudio-project/gsplat/assets/10151885/e60f7603-3c8a-4d05-a3ae-e382507eb043" width="100%" />
+  <video src="https://github.com/nerfstudio-project/gsplat/assets/10151885/64c2e9ca-a9a6-4c7e-8d6f-47eeacd15159" width="100%" />
 </div>
 
 ## Installation
 
 **Dependence**: Please install [Pytorch](https://pytorch.org/get-started/locally/) first.
 
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 The easiest way is to install from PyPI. In this way it will build the CUDA code **on the first run** (JIT).
 
 ```bash