14 citations · 14 across the 4 of their papers we have counts for
4 papers
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…
Guide-and-Rescale: Self-Guidance Mechanism for Effective Tuning-Free Real Image Editing
Vadim Titov, Madina Khalmatova, Alexandra Ivanova +2
Despite recent advances in large-scale text-to-image generative models, manipulating real images with these models remains a challenging problem. The main limitations of existing e…
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…