# 1. Contrastive to MAE

# 2. More Diversity: student network?

# 3. Diffusion to Implement Network

# 4. How to Make use of More Information of the Network

# 5. Use features in the model to identify whether an image is trained in the network


# 1. How to Select:

* 1. clustering algrithm, clip selection
  2. contrastive learning(with various data augmentations)

# 2. How to Loss:

* 1. more realistic loss
* 2. more batch loss
*  



![1701173647379](image/Ideas/1701173647379.png)

![1701173652575](image/Ideas/1701173652575.png)

![1701173660062](image/Ideas/1701173660062.png)

![1701173700755](image/Ideas/1701173700755.png)

![1701173713384](image/Ideas/1701173713384.png)