Video Content Customization Using First Frame
194
stars
42
commits
Python
primary language
Mar 17, 2026
updated
Official repository for the CVPR 2026 Paper, "First Frame is the Place to Go For Video Content Custimization"
English: [Website] | [Paper] | [🔴 YouTube: Unofficial Community Showcase] | [🔴 Real User Demo]

🤗 Lora Adapters on Huggingface:
Please note that we currently provide only a subset of our 50 training videos to demonstrate the data format.
Check the /Data/train/ folder
conda create -n ffgo python=3.11
conda activate ffgo
git clone https://github.com/zli12321/FFGO-Video-Customization.git
cd FFGO-Video-Customization
bash setup.sh
When running on your own data, make sure to append our learned transition phrase, "ad23r2 the camera view suddenly changes. ", to your text prompt to ensure the model behaves correctly.
All video results in the paper are generated at 1280 × 720 resolution with 81 frames, which requires an H200 GPU for inference unless memory-saving techniques are applied. For lower resource usage, 640 × 480 resolution videos can be generated without H200. However outputs at this lower resolution can differ significantly in content from the 1280 × 720 results as we shown in the paper.
We are using H200 (141GB RAM) to run inference. If you are using A100 or H100, the memory saving such as cpu offload features need to be turned on.
bash download.sh
bash ./example_single_inference.sh
bash example_inference.sh
@article{chen2025first,
title={First Frame Is the Place to Go for Video Content Customization},
author={Chen, Jingxi and Li, Zongxia and Liu, Zhichao and Shi, Guangyao and Wu, Xiyang and Liu, Fuxiao and Fermuller, Cornelia and Feng, Brandon Y and Aloimonos, Yiannis},
journal={arXiv preprint arXiv:2511.15700},
year={2025}
}
23 commits
19 commits
Python
97.9%
Shell
1.7%
Video Content Customization Using First Frame
194
stars
42
commits
Python
primary language
Mar 17, 2026
updated
Official repository for the CVPR 2026 Paper, "First Frame is the Place to Go For Video Content Custimization"
English: [Website] | [Paper] | [🔴 YouTube: Unofficial Community Showcase] | [🔴 Real User Demo]

🤗 Lora Adapters on Huggingface:
Please note that we currently provide only a subset of our 50 training videos to demonstrate the data format.
Check the /Data/train/ folder
conda create -n ffgo python=3.11
conda activate ffgo
git clone https://github.com/zli12321/FFGO-Video-Customization.git
cd FFGO-Video-Customization
bash setup.sh
When running on your own data, make sure to append our learned transition phrase, "ad23r2 the camera view suddenly changes. ", to your text prompt to ensure the model behaves correctly.
All video results in the paper are generated at 1280 × 720 resolution with 81 frames, which requires an H200 GPU for inference unless memory-saving techniques are applied. For lower resource usage, 640 × 480 resolution videos can be generated without H200. However outputs at this lower resolution can differ significantly in content from the 1280 × 720 results as we shown in the paper.
We are using H200 (141GB RAM) to run inference. If you are using A100 or H100, the memory saving such as cpu offload features need to be turned on.
bash download.sh
bash ./example_single_inference.sh
bash example_inference.sh
@article{chen2025first,
title={First Frame Is the Place to Go for Video Content Customization},
author={Chen, Jingxi and Li, Zongxia and Liu, Zhichao and Shi, Guangyao and Wu, Xiyang and Liu, Fuxiao and Fermuller, Cornelia and Feng, Brandon Y and Aloimonos, Yiannis},
journal={arXiv preprint arXiv:2511.15700},
year={2025}
}
23 commits
19 commits
Python
97.9%
Shell
1.7%