43 citations · 71 across the 29 of their papers we have counts for
4 papers · 1 filter
CLEAR: Character Unlearning in Textual and Visual Modalities
Alexey Dontsov, Dmitrii Korzh, Alexey Zhavoronkin +6
Machine Unlearning (MU) is critical for removing private or hazardous information from deep learning models. While MU has advanced significantly in unimodal (text or vision) settin…
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…
Group and Shuffle: Efficient Structured Orthogonal Parametrization
Mikhail Gorbunov, Nikolay Yudin, Vera Soboleva +3
The increasing size of neural networks has led to a growing demand for methods of efficient fine-tuning. Recently, an orthogonal fine-tuning paradigm was introduced that uses ortho…
HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach
Maxim Nikolaev, Mikhail Kuznetsov, Dmitry Vetrov +1
Our paper addresses the complex task of transferring a hairstyle from a reference image to an input photo for virtual hair try-on. This task is challenging due to the need to adapt…