# StructuReiser: A Structure-preserving Video Stylization Method

arXiv: https://arxiv.org/abs/2409.15341 · HTML: https://mlsanity.com/paper/2409.15341/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 26 of its 45 references that are in the map.
- First posted on arXiv 9 Sep 2024.

## Builds on (most cited first, 26 of 26)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [DreamFusion: Text-to-3D using 2D Diffusion](https://mlsanity.com/paper/2209.14988/) (2022)
- [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://mlsanity.com/paper/1603.08155/) (2016)
- [Instance Normalization: The Missing Ingredient for Fast Stylization](https://mlsanity.com/paper/1607.08022/) (2016)
- [First Order Motion Model for Image Animation](https://mlsanity.com/paper/2003.00196/) (2020)
- [UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models](https://mlsanity.com/paper/2302.04867/) (2023)
- [TokenFlow: Consistent Diffusion Features for Consistent Video Editing](https://mlsanity.com/paper/2307.10373/) (2023)
- [Universal Style Transfer via Feature Transforms](https://mlsanity.com/paper/1705.08086/) (2017)
- [Pix2Video: Video Editing using Image Diffusion](https://mlsanity.com/paper/2303.12688/) (2023)
- [Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation](https://mlsanity.com/paper/2306.07954/) (2023)
- [Few-Shot Unsupervised Image-to-Image Translation](https://mlsanity.com/paper/1905.01723/) (2019)
- [Animating Arbitrary Objects via Deep Motion Transfer](https://mlsanity.com/paper/1812.08861/) (2018)
- [Few-shot Video-to-Video Synthesis](https://mlsanity.com/paper/1910.12713/) (2019)
- [Style Transfer by Relaxed Optimal Transport and Self-Similarity](https://mlsanity.com/paper/1904.12785/) (2019)
- [Layered Neural Atlases for Consistent Video Editing](https://mlsanity.com/paper/2109.11418/) (2021)
- [Coherent Online Video Style Transfer](https://mlsanity.com/paper/1703.09211/) (2017)
- [Edit-A-Video: Single Video Editing with Object-Aware Consistency](https://mlsanity.com/paper/2303.07945/) (2023)
- [Artistic style transfer for videos and spherical images](https://mlsanity.com/paper/1708.04538/) (2017)
- [Interactive Video Stylization Using Few-Shot Patch-Based Training](https://mlsanity.com/paper/2004.14489/) (2020)
- [InFusion: Inject and Attention Fusion for Multi Concept Zero-Shot Text-based Video Editing](https://mlsanity.com/paper/2308.00135/) (2023)
- [MeDM: Mediating Image Diffusion Models for Video-to-Video Translation with Temporal Correspondence Guidance](https://mlsanity.com/paper/2308.10079/) (2023)
- [STALP: Style Transfer with Auxiliary Limited Pairing](https://mlsanity.com/paper/2110.10501/) (2021)

## Built on by (most cited first, 2 of 2)

- [ID-V2V: Identity-Preserving Video Restylization](https://mlsanity.com/paper/2607.22830/) (2026)
- [Unwarping the Lens: A Physics-Grounded Approach to Video Glasses Removal](https://mlsanity.com/paper/2608.20212/) (2026)

## Abstract (arXiv)

We introduce StructuReiser, a novel video-to-video translation method that transforms input videos into stylized sequences using a set of user-provided keyframes. Unlike existing approaches, StructuReiser maintains strict adherence to the structural elements of the target video, preserving the original identity while seamlessly applying the desired stylistic transformations. This enables a level of control and consistency that was previously unattainable with traditional text-driven or keyframe-based methods. Furthermore, StructuReiser supports real-time inference and custom keyframe editing, making it ideal for interactive applications and expanding the possibilities for creative expression and video manipulation.