collaborators

6 papers

cs.CV2026

NABLA: Neighborhood Adaptive Block-Level Attention

Dmitrii Mikhailov, Aleksey Letunovskiy, Maria Kovaleva +6

Recent progress in transformer-based architectures has demonstrated remarkable success in video generation tasks. However, the quadratic complexity of full attention mechanisms rem…

cs.CV2026

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…

cs.CV2026

Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation

Vladimir Arkhipkin, Vladimir Korviakov, Nikolai Gerasimenko +22

This report introduces Kandinsky 5.0, a family of state-of-the-art foundation models for high-resolution image and 10-second video synthesis. The framework comprises three core lin…

cs.CV2025

VIVAT: Virtuous Improving VAE Training through Artifact Mitigation

Lev Novitskiy, Viacheslav Vasilev, Maria Kovaleva +2

Variational Autoencoders (VAEs) remain a cornerstone of generative computer vision, yet their training is often plagued by artifacts that degrade reconstruction and generation qual…

cs.CV2025

GHOST 2.0: generative high-fidelity one shot transfer of heads

Alexander Groshev, Anastasiia Iashchenko, Pavel Paramonov +2

While the task of face swapping has recently gained attention in the research community, a related problem of head swapping remains largely unexplored. In addition to skin color tr…

cs.CV2025

RusCode: Russian Cultural Code Benchmark for Text-to-Image Generation

Viacheslav Vasilev, Julia Agafonova, Nikolai Gerasimenko +4

Text-to-image generation models have gained popularity among users around the world. However, many of these models exhibit a strong bias toward English-speaking cultures, ignoring…