AI RESEARCH
StreamDiT: Real-Time Streaming Text-to-Video Generation
arXiv CS.AI
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ArXi:2507.03745v4 Announce Type: replace-cross Recently, great progress has been achieved in text-to-video (T2V) generation by scaling transformer-based diffusion models to billions of parameters, which can generate high-quality videos. However, existing models typically produce only short clips offline, restricting their use cases in interactive and real-time applications. This paper addresses these challenges by proposing StreamDiT, a streaming video generation model. StreamDiT