DiT as Real-Time Rerenderer: Streaming Video Stylization with Autoregressive Diffusion Transformer
Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization holds important research value in areas such as immersive applications and artistic creation, attracting widespread attention. However, existing diffusion-based video stylization methods struggle to maintain stability and consistency when processing long videos, and their high computational cost and multi-step denoising make them difficult to apply in practical scenarios. In this work, we propose RTR-DiT (DiT as Real-Time Rerenderer), a steaming video stylization framework built upon Diffusion Transformer. We first fine-tune a bidirectional...
| Authors | Hengye Lyu, Zisu Li, Yue Hong et al. |
|---|---|
| Primary category | cs.CV |
| Published | 15 April 2026 |
| Last updated at source | 15 April 2026 |
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