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Vidu S1 represents a significant advancement in generative video technology by enabling real-time, voice-controlled interaction with digital characters on standard consumer hardware. The model's architecture leverages TurboDiffusion and TurboServe to maintain high frame rates without the typical visual degradation seen in long-form generation tasks. This development shifts interactive media creation from post-production workflows to immediate, conversational control of synthetic content.

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Vidu S1: A Real-Time Interactive Video Generation Model

arXivJuly 22, 20262 min read

arXiv:2607.03118v2 Announce Type: replace-cross Abstract: We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment through voice instructions. Vidu S1 supports infinite-length real-time video generation without blurring, drift, or visual distortion. Built with TurboDiffusion and TurboServe, Vidu S1 outputs 540p real-time videos at up to 42 FPS on regular consumer GPUs. Users can upload custom images of real people, anime, and pets, and choose different voice tones for personalized experiences. Experiments show that Vidu S1 achieves the best performance across all test metrics while fully meeting real-time inference requirements. A playable online demo is available at https://vidu.com/vidu-stream.

Abstract:We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment through voice instructions. Vidu S1 supports infinite-length real-time video generation without blurring, drift, or visual distortion. Built with TurboDiffusion and TurboServe, Vidu S1 outputs 540p real-time videos at up to 42 FPS on regular consumer GPUs. Users can upload custom images of real people, anime, and pets, and choose different voice tones for personalized experiences. Experiments show that Vidu S1 achieves the best performance across all test metrics while fully meeting real-time inference requirements. A playable online demo is available at this https URL.

Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)

arXiv:2607.03118 [cs.CV]

(or arXiv:2607.03118v2 [cs.CV] for this version)

Full text under the publisher's open licence · 126 words

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