Control-A-Video: Controllable Text-to-Video Generation with Diffusion Models
Paper • 2305.13840 • Published • 5
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("weifeng-chen/controlavideo-hed", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]- Hed Control Pretrained model for control-a-video
- Project page: https://controlavideo.github.io/
- Code: https://github.com/Weifeng-Chen/control-a-video
Citation
@misc{chen2023controlavideo,
title={Control-A-Video: Controllable Text-to-Video Generation with Diffusion Models},
author={Weifeng Chen and Jie Wu and Pan Xie and Hefeng Wu and Jiashi Li and Xin Xia and Xuefeng Xiao and Liang Lin},
year={2023},
eprint={2305.13840},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
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