ZDySS -- Zero-Shot Dynamic Scene Stylization using Gaussian Splatting
- URL: http://arxiv.org/abs/2501.03875v1
- Date: Tue, 07 Jan 2025 15:39:02 GMT
- Title: ZDySS -- Zero-Shot Dynamic Scene Stylization using Gaussian Splatting
- Authors: Abhishek Saroha, Florian Hofherr, Mariia Gladkova, Cecilia Curreli, Or Litany, Daniel Cremers,
- Abstract summary: Stylizing a dynamic scene based on an exemplar image is critical for various real-world applications, including gaming filmmaking, and augmented and virtual reality.<n>We introduceDySS, a zero-shot stylization framework for dynamic scenes, allowing our model to generalize to previously unseen style images at inference.<n>Our method demonstrates performance and coherence over state-of-the-art baselines in tests on real-world dynamic scenes, making it a robust solution for practical applications.
- Score: 41.678269742147066
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Stylizing a dynamic scene based on an exemplar image is critical for various real-world applications, including gaming, filmmaking, and augmented and virtual reality. However, achieving consistent stylization across both spatial and temporal dimensions remains a significant challenge. Most existing methods are designed for static scenes and often require an optimization process for each style image, limiting their adaptability. We introduce ZDySS, a zero-shot stylization framework for dynamic scenes, allowing our model to generalize to previously unseen style images at inference. Our approach employs Gaussian splatting for scene representation, linking each Gaussian to a learned feature vector that renders a feature map for any given view and timestamp. By applying style transfer on the learned feature vectors instead of the rendered feature map, we enhance spatio-temporal consistency across frames. Our method demonstrates superior performance and coherence over state-of-the-art baselines in tests on real-world dynamic scenes, making it a robust solution for practical applications.
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