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---
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license: apache-2.0
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---
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license: apache-2.0
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library_name: diffusers
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tags:
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- computer-vision
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- video-editing
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- video-to-video
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- diffusion
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- flow-matching
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- cvpr2026
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---
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# [CVPR 2026] PropFly: Learning to Propagate via On-the-Fly Supervision from Pre-trained Video Diffusion Models
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<div align="left">
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<a href="https://kaist-viclab.github.io/PropFly_site/"><img src="https://img.shields.io/badge/Project-Page-blue" alt="Project Page"></a>
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<a href="https://arxiv.org/abs/2602.20583"><img src="https://img.shields.io/badge/arXiv-2602.20583-b31b1b.svg" alt="arXiv"></a>
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<a href="https://github.com/pmjames16/PropFly"><img src="https://img.shields.io/badge/GitHub-Code-black?logo=github" alt="GitHub"></a>
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</div>
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Official model weights for **PropFly**.
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PropFly is a novel training pipeline for propagation-based video editing that eliminates the need for large-scale, paired (source and edited) video datasets. Instead, it leverages on-the-fly supervision from pre-trained Video Diffusion Models (VDMs).
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## Model Description
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Propagation-based video editing enables precise user control by propagating a single edited frame into subsequent frames while maintaining the original context. Our proposed method, **PropFly**, achieves this by:
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1. **On-the-Fly Supervision:** Utilizing a frozen pre-trained VDM to synthesize structurally aligned yet semantically distinct source (low-CFG) and target (high-CFG) latent pairs on the fly.
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2. **Guidance-Modulated Flow Matching (GMFM):** Training an adapter to learn propagation by predicting the VDM's high-CFG velocity, conditioned on the source video structure and the edited first frame style via GMFM loss.
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This approach ensures temporally consistent and dynamic transformations, significantly outperforming state-of-the-art methods on various video editing tasks (evaluated on EditVerseBench and TGVE benchmarks).
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## Repository Structure
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The model weights are stored in the `PropFly-1.3B/` directory.
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```text
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βββ PropFly-1.3B/
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β βββ diffusion_pytorch_model.bin # Model weights
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βββ .gitattributes
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βββ README.md
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```
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## Citation
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```text
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@article{seo2026propfly,
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title={PropFly: Learning to Propagate via On-the-Fly Supervision from Pre-trained Video Diffusion Models},
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author={Seo, Wonyong and Moon, Jaeho and Lee, Jaehyup and Kim, Soo Ye and Kim, Munchurl},
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journal={arXiv preprint arXiv:2602.20583},
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year={2026}
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}
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```
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