Update README.md

README.md

@@ -1,5 +1,13 @@
 ---
 license: apache-2.0
+language:
+- en
+tags:
+- Video-Generation
+---
+
+Certainly! Here's the text formatted for a Hugging Face README, using Markdown and LaTeX for the mathematical expression:
+
 ---
 
 ## 📷 MultiCamVideo Dataset
@@ -37,24 +45,26 @@ We take the character's position as the center of a hemisphere with a radius of
   The camera rotation angles are randomly selected within the range, with pan angles ranging from 5 to 45 degrees and tilt angles ranging from 5 to 30 degrees, with directions randomly chosen left/right or up/down.
 
 - **Basic Translation**:  
-  The camera translates along the positive and negative directions of the xyz axes, with movement distances randomly selected within the range of $[\frac{1}{4}, 1] \times \text{distance2character}$.
+  The camera translates along the positive and negative directions of the xyz axes, with movement distances randomly selected within the range of \\([\frac{1}{4}, 1] \times\\) distance2character.
 
 - **Basic Arc Trajectory**:  
   The camera moves along an arc, with rotation angles randomly selected within the range of 15 to 75 degrees.
 
 - **Random Trajectories**:  
-  1-3 points are sampled in space, and the camera moves from the initial position through these points as the movement trajectory, with the total movement distance randomly selected within the range of $[\frac{1}{4}, 1] \times \text{distance2character}$. The polyline is smoothed to make the movement more natural.
+  1-3 points are sampled in space, and the camera moves from the initial position through these points as the movement trajectory, with the total movement distance randomly selected within the range of \\([\frac{1}{4}, 1] \times\\) distance2character. The polyline is smoothed to make the movement more natural.
 
 - **Static Camera**:  
   The camera does not translate or rotate during shooting, maintaining a fixed position.
 
 3. Camera Movement Speed.
 
-To further enhance the diversity of trajectories, 50% of the training data uses constant-speed camera trajectories, while the other 50% uses variable-speed trajectories generated by nonlinear functions. Consider a camera trajectory with a total of $f$ frames, starting at location $L_{start}$ and ending at position $L_{end}$. The location at the $i$-th frame is given by:
-```math
-L_i = L_{start} + (L_{end} - L_{start}) \cdot \left( \frac{1 - \exp(-a \cdot i/f)}{1 - \exp(-a)} \right),
-```
-where $a$ is an adjustable parameter to control the trajectory speed. When $a > 0$, the trajectory starts fast and then slows down; when $a < 0$, the trajectory starts slow and then speeds up. The larger the absolute value of $a$, the more drastic the change.
+To further enhance the diversity of trajectories, 50% of the training data uses constant-speed camera trajectories, while the other 50% uses variable-speed trajectories generated by nonlinear functions. Consider a camera trajectory with a total of \\(f\\) frames, starting at location \\(L_{start}\\) and ending at position \\(L_{end}\\). The location at the \\(i\\)-th frame is given by:
+
+\\(L_i = L_{start} + (L_{end} - L_{start}) \cdot \left( \frac{1 - \exp(-a \cdot i/f)}{1 - \exp(-a)} \right),\\)
+
+where \\(a\\) is an adjustable parameter to control the trajectory speed. When \\(a > 0\\), the trajectory starts fast and then slows down; when \\(a < 0\\), the trajectory starts slow and then speeds up. The larger the absolute value of \\(a\\), the more drastic the change. 
+
+
 
 4. Camera Parameters.
 
@@ -152,4 +162,4 @@ If you found this dataset useful, please cite our [paper](https://arxiv.org/abs/
 [jianghongbai@zju.edu.cn](jianghongbai@zju.edu.cn)
 
 # Acknowledgments
-We thank Jinwen Cao, Yisong Guo, Haowen Ji, Jichao Wang, and Yi Wang from Kuaishou Technology for their invaluable help in constructing the MultiCamVideo Dataset.
+We thank Jinwen Cao, Yisong Guo, Haowen Ji, Jichao Wang, and Yi Wang from Kuaishou Technology for their invaluable help in constructing the MultiCamVideo Dataset.