2 citations · 12 across the 16 of their papers we have counts for
4 papers · 1 filter
Kandinsky S2V 1.0: Audio-Driven Avatar Video Generation
Nikolay Semenov, Artem Riabinin, Sergey Bassenko +8
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 Kandinsk…
Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation
Team Kandinsky, Julia Agafonova, Bulat Akhmatov +85
We present Kandinsky 6.0 Video, a family of foundation diffusion models for synchronized text-to-audio-video generation, comprising Kandinsky 6.0 Video Lite (3B parameters) and Kan…
Adding Voice Cloning to Text-to-Audio-Video Models with a Single Zero-Initialised Layer
Ivan Mikheev, Viacheslav Vasilev, Anna Dmitrienko +4
Text-to-audio-video (T2AV) generation models produce a video and its soundtrack from a textual description, but offer no control over whose voice speaks in the output. We show that…
Making Time Editable in Video Diffusion Transformers
Konstantin Kuklev, Viacheslav Vasilev, Alexander Kunitsyn +2
Modern Diffusion Transformers for video generation provide limited control over the progression of time and the editing of temporal dynamics. We propose a temporal-control methodol…