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The official implementation of CVPR'25 Oral paper "Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise"
| Date | Stars |
|---|---|
| 2026-07-31 | 1089 |
| 2026-08-03 | 1090 |
| 2026-08-06 | 1090 |
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<!-- # Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise --> <p align="center"> <img src="assets/Logo.png" alt="Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise" width="100%"> </p> <h1> Accepted to CVPR 2025 as Oral </h1> [](https://eyeline-labs.github.io/Go-with-the-Flow/) [](https://arxiv.org/abs/2501.08331) [](https://www.youtube.com/watch?v=IO3pbQpT5F8) [](https://huggingface.co/Eyeline-Labs/Go-with-the-Flow/tree/main) [Ryan Burgert](https://ryanndagreat.github.io)<sup>1,3</sup>, [Yuancheng Xu](https://yuancheng-xu.github.io)<sup>1,4</sup>, [Wenqi Xian](https://www.cs.cornell.edu/~wenqixian/)<sup>1</sup>, [Oliver Pilarski](https://www.linkedin.com/in/oliverpilarski/)<sup>1</sup>, [Pascal Clausen](https://www.linkedin.com/in/pascal-clausen-a179566a/?originalSubdomain=ch)<sup>1</sup>, [Mingming He](https://mingminghe.com/)<sup>1</sup>, [Li Ma](https://limacv.github.io/homepage/)<sup>1</sup>, [Yitong Deng](https://yitongdeng.github.io)<sup>2,5</sup>, [Lingxiao Li](https://scholar.google.com/citations?user=rxQDLWcAAAAJ&hl=en)<sup>2</sup>, [Mohsen Mousavi](www.linkedin.com/in/mohsen-mousavi-0516a03)<sup>1</sup>, [Michael Ryoo](http://michaelryoo.com)<sup>3</sup>, [Paul Debevec](https://www.pauldebevec.com)<sup>1</sup>, [Ning Yu](https://ningyu1991.github.io)<sup>1†</sup> <sup>1</sup>Netflix Eyeline Studios, <sup>2</sup>Netflix, <sup>3</sup>Stony Brook University, <sup>4</sup>University of Maryland, <sup>5</sup>Stanford University<br> <sup>†</sup>Project Lead ### Table of Contents - [Abstract](#abstract) - [Quick Start: Cut-and-drag Motion Control](#quick-start-cut-and-drag-motion-control) - [Animation Template GUI (Local)](#1-animation-template-gui-local) - [Running Video Diffusion (GPU)](#2-running-video-diffusion-gpu) - [TODO](#todo) - [Citation](#citation) - [Acknowledgement](#acknowledgement) <a name="abstract"></a> ## :book: Abstract Go-with-the-Flow is an easy and efficient way to control the motion patterns of video diffusion models. It lets a user decide how the camera and objects in a scene will move, and can even let you transfer motion patterns from one video to another. We simply fine-tune a base model — requiring no changes to the original pipeline or architecture, except: instead of using pure i.i.d. Gaussian noise, we use **warped noise** instead. Inference has exactly the same computational cost as running the base model. If you create something cool with our model - and want to share it on our website - email [email protected]. We will be creating a user-generated content section, starting with whomever submits the first video! If you like this project, please give it a ★! <a name="community-adoption"></a> ## :fire: Community Adoption A huge thank you to all who contributed - videos to be added here soon! - [Zeptaframe](https://github.com/Pablerdo/zeptaframe)) by @Pablerdo - [ComfyUI implementation](https://github.com/kijai/ComfyUI-VideoNoiseWarp) by @kijai - [HuggingFace Space #1](https://huggingface.co/spaces/fffiloni/Go-With-The-Flow) by fffiloni - [HuggingFace Space #2](https://huggingface.co/spaces/OneOverZero/Go-With-The-Flow) by Ryan Burgert - [AnimateDiff Implementation](https://huggingface.co/spacepxl/Go-with-the-Flow-AD-converted/tree/main) by spacepxl - [HunyuanVideo Implementation](https://huggingface.co/spacepxl/HunyuanVideo-GoWithTheFlow-unofficial) by spacepxl - [Cut-and-drag using SAMv2](https://github.com/Pablerdo/hexaframe-dark) and its [web interface](https://hexaframe-dark.vercel.app/) by Pablo Salamanca
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matched fp:68c7d9351627ed7c, llm:Description: 'The official implementation of CVPR'25 Oral paper "Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise"' — indicates video diffusion, motion-controllable video generation (video-generation, image-generation, multimodal).
matched fp:68c7d9351627ed7c, llm:Description: 'The official implementation of CVPR'25 Oral paper "Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise"' — indicates video diffusion, motion-controllable video generation (video-generation, image-generation, multimodal).
matched fp:68c7d9351627ed7c, llm:Description: 'The official implementation of CVPR'25 Oral paper "Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise"' — indicates video diffusion, motion-controllable video generation (video-generation, image-generation, multimodal).