assets

README.md

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 The official implementation of work "Diffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Models".
 
-### [[Project Page]](https://vita-group.github.io/Diffusion4D/) | [[Video (Youtube)]](https://www.youtube.com/watch?v=XJT-cMt_xVo) | [[Video (results)]](https://www.youtube.com/watch?v=sg7uUUfpM-c) | [[视频 (Bilibili)]](https://b23.tv/ojVe6Uv) | [[Arxiv]](https://arxiv.org/abs/2405.16645) | [[Dataset]](https://huggingface.co/datasets/hw-liang/Diffusion4D)
+#### [[Project Page]](https://vita-group.github.io/Diffusion4D/) | [[Video (Youtube)]](https://www.youtube.com/watch?v=XJT-cMt_xVo) | [[Video (results)]](https://www.youtube.com/watch?v=sg7uUUfpM-c) | [[视频 (Bilibili)]](https://b23.tv/ojVe6Uv) | [[Arxiv]](https://arxiv.org/abs/2405.16645) | [[Dataset]](https://huggingface.co/datasets/hw-liang/Diffusion4D)
 
 ## News
 - 2024.6.4:  Released rendered data from curated [objaverse-1.0](https://huggingface.co/datasets/hw-liang/Diffusion4D/tree/main/objaverse1.0_curated), including orbital videos of dynamic 3D, orbital videos of static 3D, and monocular videos from front view.
@@ -11,7 +11,7 @@ The official implementation of work "Diffusion4D: Fast Spatial-temporal Consiste
 
 
 
-# Preparation of 4D data
+# 4D Dataset Preparation
 ![dataset_video](./assets/dataset_web.gif)
 
 We collect a large-scale, high-quality dynamic 3D(4D) dataset sourced from the