Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Update Latte.md with the markdown equation content failed to render #69

Merged
merged 1 commit into from
Feb 29, 2024
Merged

Update Latte.md with the markdown equation content failed to render #69

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
2 changes: 1 addition & 1 deletion notes/Latte.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
和 [Stable Diffusion](https://stable-diffusion-art.com/how-stable-diffusion-work/) 原理基本一致，首先使用 VAE 压缩视频，提取视频 patch 组成 tokens，然后进行扩散-去噪过程，区别在于使用 Transforme r替换 U-Net 预测噪声的均值和方差，并且噪声是4维的，最后解码成视频。
![网络结构](../assets/Latte/Latte网络结构.png)

**输入**：视频片段经VAE压缩后假设为 $F·H·W·C$，编码后得到 tokens $Z$，维度为$n_f·n_h·n_w·d$， $Z$ 和位置时空位置编码 $p$ 相加构成Transformer的输入 $Z'$。
**输入**：视频片段经VAE压缩后假设为 $F·H·W·C$，编码后得到 tokens $Z$，维度为 $n_f·n_h·n_w·d$ ， $Z$ 和位置时空位置编码 $p$ 相加构成Transformer的输入 $Z'$。

**主干网**：
a）首先将输入 reshape 成 $Z_s$，维度为$n_f·t·d$，其中 $t=n_h·n_w$ ，先过空间Transoformer block，然后 reshape 成 $Z_t$，维度为$t·n_f·d$，过时间 Transformer block，循环几次。
Expand Down