43 citations · 71 across the 29 of their papers we have counts for
5 papers · 1 filter
StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation
Aibek Alanov, Vadim Titov, Maksim Nakhodnov +1
Domain adaptation of GANs is a problem of fine-tuning GAN models pretrained on a large dataset (e.g. StyleGAN) to a specific domain with few samples (e.g. painting faces, sketches,…
HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks
Aibek Alanov, Vadim Titov, Dmitry Vetrov
Domain adaptation framework of GANs has achieved great progress in recent years as a main successful approach of training contemporary GANs in the case of very limited training dat…
On Scaled Methods for Saddle Point Problems
Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev +2
Methods with adaptive scaling of different features play a key role in solving saddle point problems, primarily due to Adam's popularity for solving adversarial machine learning pr…
FFC-SE: Fast Fourier Convolution for Speech Enhancement
Ivan Shchekotov, Pavel Andreev, Oleg Ivanov +2
Fast Fourier convolution (FFC) is the recently proposed neural operator showing promising performance in several computer vision problems. The FFC operator allows employing large r…
HiFi++: a Unified Framework for Bandwidth Extension and Speech Enhancement
Pavel Andreev, Aibek Alanov, Oleg Ivanov +1
Generative adversarial networks have recently demonstrated outstanding performance in neural vocoding outperforming best autoregressive and flow-based models. In this paper, we sho…