Comments (6)
@jianlong-yuan @Bailey-24 @guyuchao @blE-lj Thanks for your interest! The code and the benchmark have been released. Feel free to ask any questions.
from llm-groundedvideodiffusion.
Working on the camera ready paper. We will release our code at about the same time.
from llm-groundedvideodiffusion.
插个眼
from llm-groundedvideodiffusion.
Hi, is there any update?
from llm-groundedvideodiffusion.
We are still organizing the code repo, which will include both the LLM text-to-DSL part and DSL-to-video part based on cross-attention control. However, similar to LMD+, we offer a simple custom pipeline that uses video gligen adapters that we trained on our own to condition ModelScope.
Here is a colab that uses the model: https://colab.research.google.com/drive/17He4bFAF8lXmT9Nfv-Sg29iKtPelDUNZ
We plan to also add the LLM part to colab soon.
The text-to-DSL part is straightforward. You can use ChatGPT website for it. The prompt is in the paper appendix.
Example:
Prompt: An image of grassland with a dog walking from the left to the right.
from llm-groundedvideodiffusion.
Hi, the work is very impressive and I'm looking forward to seeing your code, can I be informed of code release time?
from llm-groundedvideodiffusion.
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