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Kaleido: Open-Sourced Multi-Subject Reference Video Generation Model
arXiv – CS AI|Zhenxing Zhang, Jiayan Teng, Zhuoyi Yang, Tiankun Cao, Cheng Wang, Xiaotao Gu, Jie Tang, Dan Guo, Meng Wang|
🤖AI Summary
Researchers have introduced Kaleido, an open-source AI model for generating consistent videos from multiple reference images of subjects. The framework addresses key limitations in subject-to-video generation through improved data construction and a novel Reference Rotary Positional Encoding technique.
Key Takeaways
- →Kaleido is a new open-source subject-to-video generation framework that maintains consistency across multiple subjects in generated videos.
- →The model introduces Reference Rotary Positional Encoding (R-RoPE) to better integrate multiple reference images without subject confusion.
- →A dedicated data construction pipeline was developed to filter low-quality samples and synthesize diverse training data.
- →Extensive benchmarks show Kaleido significantly outperforms previous methods in consistency, fidelity, and generalization.
- →The research addresses critical shortcomings in existing S2V models including background disentanglement and multi-subject consistency issues.
#kaleido#video-generation#ai-model#open-source#subject-to-video#computer-vision#reference-encoding#arxiv#research
Read Original →via arXiv – CS AI
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