FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance
Paper • 2408.08189 • Published • 17
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image, export_to_video
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("qihoo360/FancyVideo", dtype=torch.bfloat16, device_map="cuda")
pipe.to("cuda")
prompt = "A man with short gray hair plays a red electric guitar."
image = load_image(
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
)
output = pipe(image=image, prompt=prompt).frames[0]
export_to_video(output, "output.mp4")FancyVideo
This repository is the official implementation of FancyVideo.
FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance
Jiasong Feng*, Ao Ma*, Jing Wang*, Bo Cheng, Xiaodan Liang, Dawei Leng†, Yuhui Yin(*Equal Contribution, ✝Corresponding Author)
We Are Hiring
We are seeking academic interns in the AIGC field. If interested, please send your resume to maao@360.cn.
BibTeX
@misc{feng2024fancyvideodynamicconsistentvideo,
title={FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance},
author={Jiasong Feng and Ao Ma and Jing Wang and Bo Cheng and Xiaodan Liang and Dawei Leng and Yuhui Yin},
year={2024},
eprint={2408.08189},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2408.08189},
}
License
This project is licensed under the Apache License (Version 2.0).
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