تقرير
Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics
العنوان: | Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics |
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المؤلفون: | Li, Ruining, Zheng, Chuanxia, Rupprecht, Christian, Vedaldi, Andrea |
سنة النشر: | 2024 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence |
الوصف: | We present Puppet-Master, an interactive video generative model that can serve as a motion prior for part-level dynamics. At test time, given a single image and a sparse set of motion trajectories (i.e., drags), Puppet-Master can synthesize a video depicting realistic part-level motion faithful to the given drag interactions. This is achieved by fine-tuning a large-scale pre-trained video diffusion model, for which we propose a new conditioning architecture to inject the dragging control effectively. More importantly, we introduce the all-to-first attention mechanism, a drop-in replacement for the widely adopted spatial attention modules, which significantly improves generation quality by addressing the appearance and background issues in existing models. Unlike other motion-conditioned video generators that are trained on in-the-wild videos and mostly move an entire object, Puppet-Master is learned from Objaverse-Animation-HQ, a new dataset of curated part-level motion clips. We propose a strategy to automatically filter out sub-optimal animations and augment the synthetic renderings with meaningful motion trajectories. Puppet-Master generalizes well to real images across various categories and outperforms existing methods in a zero-shot manner on a real-world benchmark. See our project page for more results: vgg-puppetmaster.github.io. Comment: Project page: https://vgg-puppetmaster.github.io/ |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2408.04631 |
رقم الأكسشن: | edsarx.2408.04631 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |