Kandinsky S2V 1.0: Audio-Driven Avatar Video Generation
We present Kandinsky S2V 1.0, an open family of speech-to-video models for controllable audio-driven human animation, comprising Kandinsky S2V 1.0 Lite (2B parameters) and Kandinsky S2V 1.0 Pro (21B parameters). From a single reference image, a speech waveform, and a text prompt, the models generate long-form 25 FPS video in which lip motion, expression, pose, and gesture follow the speech. The architecture draws text and audio conditioning from one Qwen2.5-Omni model and adds a reference-aware three-scale visual memory. Training starts from the Kandinsky 5.0 Video foundation models [1] and combines mixed reference-memory layouts with an area-adaptive face loss. The training corpus contai...
| Authors | Nikolay Semenov, Artem Riabinin, Sergey Bassenko et al. |
|---|---|
| Primary category | cs.CV |
| Published | 13 October 2026 |
| Last updated at source | 13 October 2026 |
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