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20232025
most citedUnleashing the power of novel conditional generative approaches for new materials discovery

2 citations · 3 across the 6 of their papers we have counts for

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cs.CV2025

ImageReFL: Balancing Quality and Diversity in Human-Aligned Diffusion Models

Dmitrii Sorokin, Maksim Nakhodnov, Andrey Kuznetsov +1

Recent advances in diffusion models have led to impressive image generation capabilities, but aligning these models with human preferences remains challenging. Reward-based fine-tu…

cs.CV2025

FastFace: Tuning Identity Preservation in Distilled Diffusion via Guidance and Attention

Sergey Karpukhin, Vadim Titov, Andrey Kuznetsov +1

In latest years plethora of identity-preserving adapters for a personalized generation with diffusion models have been released. Their main disadvantage is that they are dominantly…

cs.CV2024

Kandinsky 3: Text-to-Image Synthesis for Multifunctional Generative Framework

Vladimir Arkhipkin, Viacheslav Vasilev, Andrei Filatov +9

Text-to-image (T2I) diffusion models are popular for introducing image manipulation methods, such as editing, image fusion, inpainting, etc. At the same time, image-to-video (I2V)…

cs.CV20231 cited

Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion

Anton Razzhigaev, Arseniy Shakhmatov, Anastasia Maltseva +7

Text-to-image generation is a significant domain in modern computer vision and has achieved substantial improvements through the evolution of generative architectures. Among these,…

cs.CV2023

RusTitW: Russian Language Text Dataset for Visual Text in-the-Wild Recognition

Igor Markov, Sergey Nesteruk, Andrey Kuznetsov +1

Information surrounds people in modern life. Text is a very efficient type of information that people use for communication for centuries. However, automated text-in-the-wild recog…